{
 "cells": [
  {
   "cell_type": "code",
   "execution_count": 1,
   "id": "5a45dcbb-c4b5-4ea6-8bb4-4f5144e6c9fe",
   "metadata": {
    "execution": {
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     "iopub.status.idle": "2022-05-31T15:06:15.532420Z",
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    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Namespace(n_epochs=200, batch_size=256, lr=0.0005, n_cpu=8, latent_dim=100, img_size=28, channels=1, n_critic=5, clip_value=0.01, sample_interval=400)\n"
     ]
    }
   ],
   "source": [
    "import argparse\n",
    "import os\n",
    "import numpy as np\n",
    "import math\n",
    "import sys\n",
    "\n",
    "import torchvision.transforms as transforms\n",
    "from torchvision.utils import save_image\n",
    "\n",
    "from torch.utils.data import DataLoader\n",
    "from torchvision import datasets\n",
    "from torch.autograd import Variable\n",
    "\n",
    "import torch.nn as nn\n",
    "import torch.nn.functional as F\n",
    "import torch\n",
    "\n",
    "os.makedirs(\"images\", exist_ok=True)\n",
    "\n",
    "parser = argparse.ArgumentParser()\n",
    "parser.add_argument(\"--n_epochs\", type=int, default=200, help=\"number of epochs of training\")\n",
    "parser.add_argument(\"--batch_size\", type=int, default=256, help=\"size of the batches\")\n",
    "parser.add_argument(\"--lr\", type=float, default=0.0005, help=\"learning rate\")\n",
    "parser.add_argument(\"--n_cpu\", type=int, default=8, help=\"number of cpu threads to use during batch generation\")\n",
    "parser.add_argument(\"--latent_dim\", type=int, default=100, help=\"dimensionality of the latent space\")\n",
    "parser.add_argument(\"--img_size\", type=int, default=28, help=\"size of each image dimension\")\n",
    "parser.add_argument(\"--channels\", type=int, default=1, help=\"number of image channels\")\n",
    "parser.add_argument(\"--n_critic\", type=int, default=5, help=\"number of training steps for discriminator per iter\")\n",
    "parser.add_argument(\"--clip_value\", type=float, default=0.01, help=\"lower and upper clip value for disc. weights\")\n",
    "parser.add_argument(\"--sample_interval\", type=int, default=400, help=\"interval betwen image samples\")\n",
    "opt = parser.parse_args(args=[])\n",
    "print(opt)\n",
    "\n",
    "img_shape = (opt.channels, opt.img_size, opt.img_size)\n",
    "\n",
    "cuda = True if torch.cuda.is_available() else False"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 2,
   "id": "b6bc2cac-f173-4725-b9e3-741254ef41ed",
   "metadata": {
    "execution": {
     "iopub.execute_input": "2022-05-31T15:06:15.769680Z",
     "iopub.status.busy": "2022-05-31T15:06:15.768984Z",
     "iopub.status.idle": "2022-05-31T15:06:15.778294Z",
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     "shell.execute_reply.started": "2022-05-31T15:06:15.769646Z"
    },
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   "outputs": [],
   "source": [
    "class Generator(nn.Module):\n",
    "    def __init__(self):\n",
    "        super(Generator, self).__init__()\n",
    "\n",
    "        def block(in_feat, out_feat, normalize=True):\n",
    "            layers = [nn.Linear(in_feat, out_feat)]\n",
    "            if normalize:\n",
    "                layers.append(nn.BatchNorm1d(out_feat, 0.8))\n",
    "            layers.append(nn.LeakyReLU(0.2, inplace=True))\n",
    "            return layers\n",
    "\n",
    "        self.model = nn.Sequential(\n",
    "            *block(opt.latent_dim, 128, normalize=False),\n",
    "            *block(128, 256),\n",
    "            *block(256, 512),\n",
    "            *block(512, 1024),\n",
    "            nn.Linear(1024, int(np.prod(img_shape))),\n",
    "            nn.Tanh()\n",
    "        )\n",
    "\n",
    "    def forward(self, z):\n",
    "        img = self.model(z)\n",
    "        img = img.view(img.shape[0], *img_shape)\n",
    "        return img\n",
    "\n",
    "\n",
    "class Discriminator(nn.Module):\n",
    "    def __init__(self):\n",
    "        super(Discriminator, self).__init__()\n",
    "\n",
    "        self.model = nn.Sequential(\n",
    "            nn.Linear(int(np.prod(img_shape)), 512),\n",
    "            nn.LeakyReLU(0.2, inplace=True),\n",
    "            nn.Linear(512, 256),\n",
    "            nn.LeakyReLU(0.2, inplace=True),\n",
    "            nn.Linear(256, 1),\n",
    "        )\n",
    "\n",
    "    def forward(self, img):\n",
    "        img_flat = img.view(img.shape[0], -1)\n",
    "        validity = self.model(img_flat)\n",
    "        return validity"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 3,
   "id": "05387e06-923d-45f9-ab84-c79b66f3ac70",
   "metadata": {
    "execution": {
     "iopub.execute_input": "2022-05-31T15:06:16.766283Z",
     "iopub.status.busy": "2022-05-31T15:06:16.765777Z",
     "iopub.status.idle": "2022-05-31T15:06:16.828172Z",
     "shell.execute_reply": "2022-05-31T15:06:16.827636Z",
     "shell.execute_reply.started": "2022-05-31T15:06:16.766257Z"
    },
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   },
   "outputs": [],
   "source": [
    "# Initialize generator and discriminator\n",
    "generator = Generator()\n",
    "discriminator = Discriminator()\n",
    "\n",
    "if cuda:\n",
    "    generator.cuda()\n",
    "    discriminator.cuda()\n",
    "\n",
    "# Configure data loader\n",
    "os.makedirs(\"../../data/mnist\", exist_ok=True)\n",
    "dataloader = torch.utils.data.DataLoader(\n",
    "    datasets.MNIST(\n",
    "        \"../../data/mnist\",\n",
    "        train=True,\n",
    "        download=True,\n",
    "        transform=transforms.Compose([transforms.ToTensor(), transforms.Normalize([0.5], [0.5])]),\n",
    "    ),\n",
    "    batch_size=opt.batch_size,\n",
    "    shuffle=True,\n",
    ")\n",
    "\n",
    "# Optimizers\n",
    "optimizer_G = torch.optim.RMSprop(generator.parameters(), lr=opt.lr)\n",
    "optimizer_D = torch.optim.RMSprop(discriminator.parameters(), lr=opt.lr)\n",
    "\n",
    "Tensor = torch.cuda.FloatTensor if cuda else torch.FloatTensor"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 5,
   "id": "19b06cb6-6c95-4ff1-bc6e-a9e23ec95270",
   "metadata": {
    "execution": {
     "iopub.execute_input": "2022-05-31T15:06:37.766324Z",
     "iopub.status.busy": "2022-05-31T15:06:37.765669Z",
     "iopub.status.idle": "2022-05-31T15:58:46.951963Z",
     "shell.execute_reply": "2022-05-31T15:58:46.951394Z",
     "shell.execute_reply.started": "2022-05-31T15:06:37.766293Z"
    },
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   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "[Epoch 0/200] [Batch 0/235] [D loss: -1.155452] [G loss: -12.976433]\n",
      "[Epoch 0/200] [Batch 5/235] [D loss: -1.766129] [G loss: -12.659447]\n",
      "[Epoch 0/200] [Batch 10/235] [D loss: -1.391063] [G loss: -13.524946]\n",
      "[Epoch 0/200] [Batch 15/235] [D loss: -0.653810] [G loss: -14.592182]\n",
      "[Epoch 0/200] [Batch 20/235] [D loss: -0.164272] [G loss: -13.838066]\n",
      "[Epoch 0/200] [Batch 25/235] [D loss: -0.187021] [G loss: -12.376773]\n",
      "[Epoch 0/200] [Batch 30/235] [D loss: -0.523592] [G loss: -11.725918]\n",
      "[Epoch 0/200] [Batch 35/235] [D loss: -0.824333] [G loss: -11.960309]\n",
      "[Epoch 0/200] [Batch 40/235] [D loss: -0.921561] [G loss: -12.521187]\n",
      "[Epoch 0/200] [Batch 45/235] [D loss: -0.697882] [G loss: -12.399031]\n",
      "[Epoch 0/200] [Batch 50/235] [D loss: -0.629149] [G loss: -11.880112]\n",
      "[Epoch 0/200] [Batch 55/235] [D loss: -0.549687] [G loss: -11.439232]\n",
      "[Epoch 0/200] [Batch 60/235] [D loss: -0.500341] [G loss: -11.333338]\n",
      "[Epoch 0/200] [Batch 65/235] [D loss: -0.359652] [G loss: -11.694602]\n",
      "[Epoch 0/200] [Batch 70/235] [D loss: -0.459266] [G loss: -12.468794]\n",
      "[Epoch 0/200] [Batch 75/235] [D loss: -0.502523] [G loss: -13.336817]\n",
      "[Epoch 0/200] [Batch 80/235] [D loss: -0.488173] [G loss: -14.160997]\n",
      "[Epoch 0/200] [Batch 85/235] [D loss: -0.464273] [G loss: -14.730394]\n",
      "[Epoch 0/200] [Batch 90/235] [D loss: -0.224110] [G loss: -14.700487]\n",
      "[Epoch 0/200] [Batch 95/235] [D loss: -0.164310] [G loss: -13.353966]\n",
      "[Epoch 0/200] [Batch 100/235] [D loss: 0.016766] [G loss: -11.460890]\n",
      "[Epoch 0/200] [Batch 105/235] [D loss: -0.143451] [G loss: -10.071218]\n",
      "[Epoch 0/200] [Batch 110/235] [D loss: -0.318487] [G loss: -9.062553]\n",
      "[Epoch 0/200] [Batch 115/235] [D loss: -0.462380] [G loss: -8.652262]\n",
      "[Epoch 0/200] [Batch 120/235] [D loss: -0.574085] [G loss: -8.517541]\n",
      "[Epoch 0/200] [Batch 125/235] [D loss: -0.725506] [G loss: -8.134813]\n",
      "[Epoch 0/200] [Batch 130/235] [D loss: -0.647061] [G loss: -8.254643]\n",
      "[Epoch 0/200] [Batch 135/235] [D loss: -0.418391] [G loss: -8.917217]\n",
      "[Epoch 0/200] [Batch 140/235] [D loss: -0.169850] [G loss: -9.707374]\n",
      "[Epoch 0/200] [Batch 145/235] [D loss: -0.169715] [G loss: -10.172042]\n",
      "[Epoch 0/200] [Batch 150/235] [D loss: -0.182369] [G loss: -10.873662]\n",
      "[Epoch 0/200] [Batch 155/235] [D loss: -0.347659] [G loss: -12.001366]\n",
      "[Epoch 0/200] [Batch 160/235] [D loss: -0.480787] [G loss: -13.310383]\n",
      "[Epoch 0/200] [Batch 165/235] [D loss: -0.383946] [G loss: -13.973652]\n",
      "[Epoch 0/200] [Batch 170/235] [D loss: -0.106543] [G loss: -12.730685]\n",
      "[Epoch 0/200] [Batch 175/235] [D loss: -0.043135] [G loss: -10.734392]\n",
      "[Epoch 0/200] [Batch 180/235] [D loss: -0.101225] [G loss: -9.328630]\n",
      "[Epoch 0/200] [Batch 185/235] [D loss: -0.208163] [G loss: -8.349524]\n",
      "[Epoch 0/200] [Batch 190/235] [D loss: -0.194129] [G loss: -7.781405]\n",
      "[Epoch 0/200] [Batch 195/235] [D loss: -0.188930] [G loss: -7.392357]\n",
      "[Epoch 0/200] [Batch 200/235] [D loss: -0.083931] [G loss: -7.252374]\n",
      "[Epoch 0/200] [Batch 205/235] [D loss: -0.274048] [G loss: -7.386599]\n",
      "[Epoch 0/200] [Batch 210/235] [D loss: -0.206554] [G loss: -7.911505]\n",
      "[Epoch 0/200] [Batch 215/235] [D loss: -0.339459] [G loss: -8.459091]\n",
      "[Epoch 0/200] [Batch 220/235] [D loss: -0.357459] [G loss: -9.118904]\n",
      "[Epoch 0/200] [Batch 225/235] [D loss: -0.257988] [G loss: -9.602367]\n",
      "[Epoch 0/200] [Batch 230/235] [D loss: -0.146319] [G loss: -9.728944]\n",
      "[Epoch 1/200] [Batch 0/235] [D loss: 0.001852] [G loss: -8.984116]\n",
      "[Epoch 1/200] [Batch 5/235] [D loss: 0.052740] [G loss: -7.582358]\n",
      "[Epoch 1/200] [Batch 10/235] [D loss: 0.064211] [G loss: -6.492186]\n",
      "[Epoch 1/200] [Batch 15/235] [D loss: -0.024649] [G loss: -5.925553]\n",
      "[Epoch 1/200] [Batch 20/235] [D loss: -0.075693] [G loss: -5.656215]\n",
      "[Epoch 1/200] [Batch 25/235] [D loss: -0.187711] [G loss: -5.913706]\n",
      "[Epoch 1/200] [Batch 30/235] [D loss: -0.288916] [G loss: -6.599940]\n",
      "[Epoch 1/200] [Batch 35/235] [D loss: -0.280791] [G loss: -7.262130]\n",
      "[Epoch 1/200] [Batch 40/235] [D loss: -0.240528] [G loss: -7.680308]\n",
      "[Epoch 1/200] [Batch 45/235] [D loss: -0.067521] [G loss: -7.415029]\n",
      "[Epoch 1/200] [Batch 50/235] [D loss: 0.006580] [G loss: -6.721644]\n",
      "[Epoch 1/200] [Batch 55/235] [D loss: 0.023092] [G loss: -5.667062]\n",
      "[Epoch 1/200] [Batch 60/235] [D loss: -0.016201] [G loss: -4.871293]\n",
      "[Epoch 1/200] [Batch 65/235] [D loss: -0.093940] [G loss: -4.331874]\n",
      "[Epoch 1/200] [Batch 70/235] [D loss: -0.106753] [G loss: -4.074407]\n",
      "[Epoch 1/200] [Batch 75/235] [D loss: -0.162138] [G loss: -4.069914]\n",
      "[Epoch 1/200] [Batch 80/235] [D loss: -0.147732] [G loss: -3.844485]\n",
      "[Epoch 1/200] [Batch 85/235] [D loss: -0.117254] [G loss: -3.588809]\n",
      "[Epoch 1/200] [Batch 90/235] [D loss: -0.106380] [G loss: -3.240427]\n",
      "[Epoch 1/200] [Batch 95/235] [D loss: -0.086000] [G loss: -2.965221]\n",
      "[Epoch 1/200] [Batch 100/235] [D loss: -0.067322] [G loss: -2.840211]\n",
      "[Epoch 1/200] [Batch 105/235] [D loss: -0.061909] [G loss: -2.809630]\n",
      "[Epoch 1/200] [Batch 110/235] [D loss: -0.049063] [G loss: -2.633335]\n",
      "[Epoch 1/200] [Batch 115/235] [D loss: -0.053494] [G loss: -2.440156]\n",
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      "[Epoch 1/200] [Batch 130/235] [D loss: -0.071316] [G loss: -1.521474]\n",
      "[Epoch 1/200] [Batch 135/235] [D loss: -0.081413] [G loss: -1.253945]\n",
      "[Epoch 1/200] [Batch 140/235] [D loss: -0.084966] [G loss: -0.826530]\n",
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      "[Epoch 1/200] [Batch 215/235] [D loss: 0.022471] [G loss: -3.279077]\n",
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      "[Epoch 1/200] [Batch 230/235] [D loss: -0.015114] [G loss: -3.179965]\n",
      "[Epoch 2/200] [Batch 0/235] [D loss: -0.028016] [G loss: -3.262539]\n",
      "[Epoch 2/200] [Batch 5/235] [D loss: -0.043487] [G loss: -3.574506]\n",
      "[Epoch 2/200] [Batch 10/235] [D loss: -0.058656] [G loss: -3.887607]\n",
      "[Epoch 2/200] [Batch 15/235] [D loss: -0.060767] [G loss: -3.975101]\n",
      "[Epoch 2/200] [Batch 20/235] [D loss: -0.007531] [G loss: -3.841636]\n",
      "[Epoch 2/200] [Batch 25/235] [D loss: -0.001390] [G loss: -3.484358]\n",
      "[Epoch 2/200] [Batch 30/235] [D loss: 0.004766] [G loss: -3.022457]\n",
      "[Epoch 2/200] [Batch 35/235] [D loss: -0.007802] [G loss: -2.759517]\n",
      "[Epoch 2/200] [Batch 40/235] [D loss: -0.013884] [G loss: -2.718634]\n",
      "[Epoch 2/200] [Batch 45/235] [D loss: -0.026110] [G loss: -2.747694]\n",
      "[Epoch 2/200] [Batch 50/235] [D loss: -0.036759] [G loss: -2.950084]\n",
      "[Epoch 2/200] [Batch 55/235] [D loss: -0.054610] [G loss: -3.118052]\n",
      "[Epoch 2/200] [Batch 60/235] [D loss: -0.050297] [G loss: -3.321812]\n",
      "[Epoch 2/200] [Batch 65/235] [D loss: -0.009045] [G loss: -3.657027]\n",
      "[Epoch 2/200] [Batch 70/235] [D loss: 0.002253] [G loss: -3.853097]\n",
      "[Epoch 2/200] [Batch 75/235] [D loss: -0.010444] [G loss: -3.935122]\n",
      "[Epoch 2/200] [Batch 80/235] [D loss: -0.007994] [G loss: -4.004453]\n",
      "[Epoch 2/200] [Batch 85/235] [D loss: -0.024604] [G loss: -4.200970]\n",
      "[Epoch 2/200] [Batch 90/235] [D loss: -0.036057] [G loss: -4.533780]\n",
      "[Epoch 2/200] [Batch 95/235] [D loss: -0.051325] [G loss: -4.865564]\n",
      "[Epoch 2/200] [Batch 100/235] [D loss: -0.039782] [G loss: -4.973971]\n",
      "[Epoch 2/200] [Batch 105/235] [D loss: 0.003310] [G loss: -4.328472]\n",
      "[Epoch 2/200] [Batch 110/235] [D loss: -0.007405] [G loss: -3.655369]\n",
      "[Epoch 2/200] [Batch 115/235] [D loss: -0.014550] [G loss: -3.483492]\n",
      "[Epoch 2/200] [Batch 120/235] [D loss: -0.041745] [G loss: -3.636064]\n",
      "[Epoch 2/200] [Batch 125/235] [D loss: -0.023772] [G loss: -3.736481]\n",
      "[Epoch 2/200] [Batch 130/235] [D loss: -0.017234] [G loss: -3.513975]\n",
      "[Epoch 2/200] [Batch 135/235] [D loss: -0.012014] [G loss: -3.246693]\n",
      "[Epoch 2/200] [Batch 140/235] [D loss: -0.000275] [G loss: -3.063771]\n",
      "[Epoch 2/200] [Batch 145/235] [D loss: -0.005790] [G loss: -2.951270]\n",
      "[Epoch 2/200] [Batch 150/235] [D loss: -0.022075] [G loss: -3.053460]\n",
      "[Epoch 2/200] [Batch 155/235] [D loss: -0.030319] [G loss: -3.439199]\n",
      "[Epoch 2/200] [Batch 160/235] [D loss: -0.037049] [G loss: -3.530134]\n",
      "[Epoch 2/200] [Batch 165/235] [D loss: -0.001809] [G loss: -3.731820]\n",
      "[Epoch 2/200] [Batch 170/235] [D loss: -0.005486] [G loss: -3.765303]\n",
      "[Epoch 2/200] [Batch 175/235] [D loss: 0.002122] [G loss: -3.636043]\n",
      "[Epoch 2/200] [Batch 180/235] [D loss: -0.014184] [G loss: -3.852185]\n",
      "[Epoch 2/200] [Batch 185/235] [D loss: -0.008138] [G loss: -3.924356]\n",
      "[Epoch 2/200] [Batch 190/235] [D loss: -0.028469] [G loss: -3.851133]\n",
      "[Epoch 2/200] [Batch 195/235] [D loss: -0.039303] [G loss: -3.702982]\n",
      "[Epoch 2/200] [Batch 200/235] [D loss: -0.027240] [G loss: -3.546395]\n",
      "[Epoch 2/200] [Batch 205/235] [D loss: -0.004245] [G loss: -2.955937]\n",
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      "[Epoch 8/200] [Batch 0/235] [D loss: -0.012374] [G loss: -2.004663]\n",
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      "[Epoch 9/200] [Batch 0/235] [D loss: -0.147267] [G loss: -2.210365]\n",
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      "[Epoch 10/200] [Batch 0/235] [D loss: -0.198351] [G loss: -2.461268]\n",
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      "[Epoch 10/200] [Batch 210/235] [D loss: -0.755138] [G loss: -2.276929]\n",
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      "[Epoch 11/200] [Batch 0/235] [D loss: -0.320626] [G loss: -0.892222]\n",
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      "[Epoch 11/200] [Batch 110/235] [D loss: -0.824138] [G loss: -0.573338]\n",
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      "[Epoch 11/200] [Batch 120/235] [D loss: -0.323529] [G loss: 0.743858]\n",
      "[Epoch 11/200] [Batch 125/235] [D loss: -0.339515] [G loss: 1.917011]\n",
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      "[Epoch 11/200] [Batch 135/235] [D loss: -0.653601] [G loss: 0.039631]\n",
      "[Epoch 11/200] [Batch 140/235] [D loss: -0.336043] [G loss: 0.307752]\n",
      "[Epoch 11/200] [Batch 145/235] [D loss: -0.381989] [G loss: 1.409959]\n",
      "[Epoch 11/200] [Batch 150/235] [D loss: -0.610784] [G loss: 0.327792]\n",
      "[Epoch 11/200] [Batch 155/235] [D loss: -0.399565] [G loss: 0.273897]\n",
      "[Epoch 11/200] [Batch 160/235] [D loss: -0.401406] [G loss: 0.186662]\n",
      "[Epoch 11/200] [Batch 165/235] [D loss: -0.571477] [G loss: 0.609022]\n",
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      "[Epoch 15/200] [Batch 0/235] [D loss: -0.427848] [G loss: -0.454618]\n",
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      "[Epoch 16/200] [Batch 0/235] [D loss: -0.131992] [G loss: -1.717750]\n",
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      "[Epoch 18/200] [Batch 0/235] [D loss: -0.230423] [G loss: 0.082741]\n",
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      "[Epoch 19/200] [Batch 0/235] [D loss: -0.202132] [G loss: -0.120398]\n",
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      "[Epoch 19/200] [Batch 135/235] [D loss: -0.313920] [G loss: 0.191797]\n",
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      "[Epoch 20/200] [Batch 0/235] [D loss: -0.231737] [G loss: 0.327893]\n",
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      "[Epoch 20/200] [Batch 155/235] [D loss: -0.276560] [G loss: -0.057222]\n",
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      "[Epoch 21/200] [Batch 205/235] [D loss: -0.217188] [G loss: -0.134575]\n",
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      "[Epoch 22/200] [Batch 0/235] [D loss: -0.193682] [G loss: 0.183773]\n",
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      "[Epoch 22/200] [Batch 75/235] [D loss: -0.261956] [G loss: -0.012096]\n",
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      "[Epoch 22/200] [Batch 85/235] [D loss: -0.283068] [G loss: 0.190155]\n",
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      "[Epoch 22/200] [Batch 100/235] [D loss: -0.351008] [G loss: 0.199188]\n",
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      "[Epoch 22/200] [Batch 115/235] [D loss: -0.243044] [G loss: 0.587712]\n",
      "[Epoch 22/200] [Batch 120/235] [D loss: -0.171294] [G loss: 0.215799]\n",
      "[Epoch 22/200] [Batch 125/235] [D loss: -0.372332] [G loss: 0.256880]\n",
      "[Epoch 22/200] [Batch 130/235] [D loss: -0.222552] [G loss: 0.555041]\n",
      "[Epoch 22/200] [Batch 135/235] [D loss: -0.218710] [G loss: 0.325907]\n",
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      "[Epoch 22/200] [Batch 145/235] [D loss: -0.254386] [G loss: 0.343326]\n",
      "[Epoch 22/200] [Batch 150/235] [D loss: -0.238607] [G loss: -0.290532]\n",
      "[Epoch 22/200] [Batch 155/235] [D loss: -0.374883] [G loss: -0.255494]\n",
      "[Epoch 22/200] [Batch 160/235] [D loss: -0.257652] [G loss: 0.032724]\n",
      "[Epoch 22/200] [Batch 165/235] [D loss: -0.249873] [G loss: -0.030603]\n",
      "[Epoch 22/200] [Batch 170/235] [D loss: -0.437369] [G loss: -0.558168]\n",
      "[Epoch 22/200] [Batch 175/235] [D loss: -0.215470] [G loss: 0.132880]\n",
      "[Epoch 22/200] [Batch 180/235] [D loss: -0.248000] [G loss: 0.336989]\n",
      "[Epoch 22/200] [Batch 185/235] [D loss: -0.282085] [G loss: 0.016786]\n",
      "[Epoch 22/200] [Batch 190/235] [D loss: -0.207607] [G loss: 0.246457]\n",
      "[Epoch 22/200] [Batch 195/235] [D loss: -0.360020] [G loss: 0.004121]\n",
      "[Epoch 22/200] [Batch 200/235] [D loss: -0.264095] [G loss: 0.132613]\n",
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      "[Epoch 22/200] [Batch 220/235] [D loss: -0.274859] [G loss: 0.229824]\n",
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      "[Epoch 22/200] [Batch 230/235] [D loss: -0.169437] [G loss: -0.061300]\n",
      "[Epoch 23/200] [Batch 0/235] [D loss: -0.180733] [G loss: -0.097012]\n",
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      "[Epoch 23/200] [Batch 15/235] [D loss: -0.303957] [G loss: -0.438546]\n",
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      "[Epoch 23/200] [Batch 40/235] [D loss: -0.155649] [G loss: -0.318765]\n",
      "[Epoch 23/200] [Batch 45/235] [D loss: -0.288521] [G loss: -0.007871]\n",
      "[Epoch 23/200] [Batch 50/235] [D loss: -0.295990] [G loss: -0.156584]\n",
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      "[Epoch 23/200] [Batch 60/235] [D loss: -0.239420] [G loss: -0.028895]\n",
      "[Epoch 23/200] [Batch 65/235] [D loss: -0.240056] [G loss: -0.173448]\n",
      "[Epoch 23/200] [Batch 70/235] [D loss: -0.227595] [G loss: -0.171729]\n",
      "[Epoch 23/200] [Batch 75/235] [D loss: -0.187855] [G loss: -0.056565]\n",
      "[Epoch 23/200] [Batch 80/235] [D loss: -0.199823] [G loss: -0.277196]\n",
      "[Epoch 23/200] [Batch 85/235] [D loss: -0.282226] [G loss: -0.251984]\n",
      "[Epoch 23/200] [Batch 90/235] [D loss: -0.244792] [G loss: -0.607954]\n",
      "[Epoch 23/200] [Batch 95/235] [D loss: -0.233752] [G loss: -0.385488]\n",
      "[Epoch 23/200] [Batch 100/235] [D loss: -0.260482] [G loss: -0.653431]\n",
      "[Epoch 23/200] [Batch 105/235] [D loss: -0.210750] [G loss: -0.371950]\n",
      "[Epoch 23/200] [Batch 110/235] [D loss: -0.238072] [G loss: -0.401113]\n",
      "[Epoch 23/200] [Batch 115/235] [D loss: -0.176693] [G loss: -0.215988]\n",
      "[Epoch 23/200] [Batch 120/235] [D loss: -0.195610] [G loss: -0.079477]\n",
      "[Epoch 23/200] [Batch 125/235] [D loss: -0.207455] [G loss: -0.295368]\n",
      "[Epoch 23/200] [Batch 130/235] [D loss: -0.203594] [G loss: -0.060466]\n",
      "[Epoch 23/200] [Batch 135/235] [D loss: -0.212395] [G loss: -0.354276]\n",
      "[Epoch 23/200] [Batch 140/235] [D loss: -0.198574] [G loss: -0.325675]\n",
      "[Epoch 23/200] [Batch 145/235] [D loss: -0.243077] [G loss: -0.966766]\n",
      "[Epoch 23/200] [Batch 150/235] [D loss: -0.259586] [G loss: -0.202997]\n",
      "[Epoch 23/200] [Batch 155/235] [D loss: -0.208848] [G loss: -0.310946]\n",
      "[Epoch 23/200] [Batch 160/235] [D loss: -0.232833] [G loss: -0.598710]\n",
      "[Epoch 23/200] [Batch 165/235] [D loss: -0.351418] [G loss: -0.246405]\n",
      "[Epoch 23/200] [Batch 170/235] [D loss: -0.175688] [G loss: -0.323324]\n",
      "[Epoch 23/200] [Batch 175/235] [D loss: -0.236857] [G loss: -0.418053]\n",
      "[Epoch 23/200] [Batch 180/235] [D loss: -0.185394] [G loss: -0.173477]\n",
      "[Epoch 23/200] [Batch 185/235] [D loss: -0.216838] [G loss: 0.178927]\n",
      "[Epoch 23/200] [Batch 190/235] [D loss: -0.203123] [G loss: 0.156668]\n",
      "[Epoch 23/200] [Batch 195/235] [D loss: -0.264887] [G loss: -0.059939]\n",
      "[Epoch 23/200] [Batch 200/235] [D loss: -0.249830] [G loss: 0.063059]\n",
      "[Epoch 23/200] [Batch 205/235] [D loss: -0.239323] [G loss: 0.043127]\n",
      "[Epoch 23/200] [Batch 210/235] [D loss: -0.144274] [G loss: -0.642772]\n",
      "[Epoch 23/200] [Batch 215/235] [D loss: -0.435490] [G loss: -0.032733]\n",
      "[Epoch 23/200] [Batch 220/235] [D loss: -0.206183] [G loss: 0.200335]\n",
      "[Epoch 23/200] [Batch 225/235] [D loss: -0.206393] [G loss: 0.277343]\n",
      "[Epoch 23/200] [Batch 230/235] [D loss: -0.203418] [G loss: -0.343220]\n",
      "[Epoch 24/200] [Batch 0/235] [D loss: -0.335042] [G loss: -0.154604]\n",
      "[Epoch 24/200] [Batch 5/235] [D loss: -0.248006] [G loss: 0.320436]\n",
      "[Epoch 24/200] [Batch 10/235] [D loss: -0.164217] [G loss: -0.175717]\n",
      "[Epoch 24/200] [Batch 15/235] [D loss: -0.244105] [G loss: 0.271393]\n",
      "[Epoch 24/200] [Batch 20/235] [D loss: -0.278737] [G loss: -0.083100]\n",
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      "[Epoch 24/200] [Batch 30/235] [D loss: -0.202731] [G loss: -0.342049]\n",
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      "[Epoch 24/200] [Batch 45/235] [D loss: -0.225511] [G loss: -0.235465]\n",
      "[Epoch 24/200] [Batch 50/235] [D loss: -0.326786] [G loss: -0.449624]\n",
      "[Epoch 24/200] [Batch 55/235] [D loss: -0.280022] [G loss: 0.154038]\n",
      "[Epoch 24/200] [Batch 60/235] [D loss: -0.197425] [G loss: -0.283137]\n",
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      "[Epoch 24/200] [Batch 70/235] [D loss: -0.342630] [G loss: -0.276116]\n",
      "[Epoch 24/200] [Batch 75/235] [D loss: -0.240540] [G loss: -0.109382]\n",
      "[Epoch 24/200] [Batch 80/235] [D loss: -0.218248] [G loss: -0.238641]\n",
      "[Epoch 24/200] [Batch 85/235] [D loss: -0.409552] [G loss: -0.588781]\n",
      "[Epoch 24/200] [Batch 90/235] [D loss: -0.239486] [G loss: -0.029529]\n",
      "[Epoch 24/200] [Batch 95/235] [D loss: -0.202528] [G loss: -0.209659]\n",
      "[Epoch 24/200] [Batch 100/235] [D loss: -0.311203] [G loss: -0.396288]\n",
      "[Epoch 24/200] [Batch 105/235] [D loss: -0.213300] [G loss: 0.104004]\n",
      "[Epoch 24/200] [Batch 110/235] [D loss: -0.191779] [G loss: -0.246601]\n",
      "[Epoch 24/200] [Batch 115/235] [D loss: -0.328935] [G loss: -0.387053]\n",
      "[Epoch 24/200] [Batch 120/235] [D loss: -0.225704] [G loss: -0.020912]\n",
      "[Epoch 24/200] [Batch 125/235] [D loss: -0.230591] [G loss: -0.223546]\n",
      "[Epoch 24/200] [Batch 130/235] [D loss: -0.320684] [G loss: -0.509106]\n",
      "[Epoch 24/200] [Batch 135/235] [D loss: -0.222991] [G loss: 0.277919]\n",
      "[Epoch 24/200] [Batch 140/235] [D loss: -0.212662] [G loss: -0.230785]\n",
      "[Epoch 24/200] [Batch 145/235] [D loss: -0.299847] [G loss: -0.242580]\n",
      "[Epoch 24/200] [Batch 150/235] [D loss: -0.184751] [G loss: 0.180110]\n",
      "[Epoch 24/200] [Batch 155/235] [D loss: -0.256909] [G loss: -0.004677]\n",
      "[Epoch 24/200] [Batch 160/235] [D loss: -0.183620] [G loss: -0.221144]\n",
      "[Epoch 24/200] [Batch 165/235] [D loss: -0.241249] [G loss: -0.426186]\n",
      "[Epoch 24/200] [Batch 170/235] [D loss: -0.290871] [G loss: -0.325953]\n",
      "[Epoch 24/200] [Batch 175/235] [D loss: -0.222722] [G loss: -0.868924]\n",
      "[Epoch 24/200] [Batch 180/235] [D loss: -0.293001] [G loss: -0.396535]\n",
      "[Epoch 24/200] [Batch 185/235] [D loss: -0.162054] [G loss: -0.098684]\n",
      "[Epoch 24/200] [Batch 190/235] [D loss: -0.242839] [G loss: 0.314308]\n",
      "[Epoch 24/200] [Batch 195/235] [D loss: -0.313309] [G loss: -0.002226]\n",
      "[Epoch 24/200] [Batch 200/235] [D loss: -0.394395] [G loss: -0.489458]\n",
      "[Epoch 24/200] [Batch 205/235] [D loss: -0.178803] [G loss: 0.159562]\n",
      "[Epoch 24/200] [Batch 210/235] [D loss: -0.230992] [G loss: 0.180154]\n",
      "[Epoch 24/200] [Batch 215/235] [D loss: -0.323420] [G loss: -0.019552]\n",
      "[Epoch 24/200] [Batch 220/235] [D loss: -0.228300] [G loss: 0.067332]\n",
      "[Epoch 24/200] [Batch 225/235] [D loss: -0.206792] [G loss: -0.135436]\n",
      "[Epoch 24/200] [Batch 230/235] [D loss: -0.222333] [G loss: -0.245685]\n",
      "[Epoch 25/200] [Batch 0/235] [D loss: -0.241568] [G loss: -0.117257]\n",
      "[Epoch 25/200] [Batch 5/235] [D loss: -0.214577] [G loss: 0.195901]\n",
      "[Epoch 25/200] [Batch 10/235] [D loss: -0.255315] [G loss: -0.131662]\n",
      "[Epoch 25/200] [Batch 15/235] [D loss: -0.306931] [G loss: -0.163383]\n",
      "[Epoch 25/200] [Batch 20/235] [D loss: -0.226637] [G loss: -0.065591]\n",
      "[Epoch 25/200] [Batch 25/235] [D loss: -0.254859] [G loss: 0.036385]\n",
      "[Epoch 25/200] [Batch 30/235] [D loss: -0.379061] [G loss: -0.698786]\n",
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      "[Epoch 26/200] [Batch 0/235] [D loss: -0.254397] [G loss: -0.475016]\n",
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      "[Epoch 26/200] [Batch 65/235] [D loss: -0.293740] [G loss: -0.410411]\n",
      "[Epoch 26/200] [Batch 70/235] [D loss: -0.236333] [G loss: -0.086426]\n",
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      "[Epoch 26/200] [Batch 80/235] [D loss: -0.249445] [G loss: 0.226761]\n",
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      "[Epoch 26/200] [Batch 135/235] [D loss: -0.206855] [G loss: -0.005869]\n",
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      "[Epoch 26/200] [Batch 155/235] [D loss: -0.413964] [G loss: -0.357359]\n",
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      "[Epoch 26/200] [Batch 165/235] [D loss: -0.240523] [G loss: -0.062271]\n",
      "[Epoch 26/200] [Batch 170/235] [D loss: -0.184322] [G loss: -0.261459]\n",
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      "[Epoch 26/200] [Batch 195/235] [D loss: -0.257346] [G loss: -0.269985]\n",
      "[Epoch 26/200] [Batch 200/235] [D loss: -0.168076] [G loss: -0.237221]\n",
      "[Epoch 26/200] [Batch 205/235] [D loss: -0.260279] [G loss: -0.176680]\n",
      "[Epoch 26/200] [Batch 210/235] [D loss: -0.264363] [G loss: -0.069250]\n",
      "[Epoch 26/200] [Batch 215/235] [D loss: -0.156509] [G loss: -0.139474]\n",
      "[Epoch 26/200] [Batch 220/235] [D loss: -0.409464] [G loss: -0.125930]\n",
      "[Epoch 26/200] [Batch 225/235] [D loss: -0.184936] [G loss: 0.519873]\n",
      "[Epoch 26/200] [Batch 230/235] [D loss: -0.209013] [G loss: -0.082112]\n",
      "[Epoch 27/200] [Batch 0/235] [D loss: -0.258365] [G loss: -0.465051]\n",
      "[Epoch 27/200] [Batch 5/235] [D loss: -0.235207] [G loss: 0.036647]\n",
      "[Epoch 27/200] [Batch 10/235] [D loss: -0.213271] [G loss: -0.071162]\n",
      "[Epoch 27/200] [Batch 15/235] [D loss: -0.240527] [G loss: -0.261486]\n",
      "[Epoch 27/200] [Batch 20/235] [D loss: -0.200852] [G loss: -0.016314]\n",
      "[Epoch 27/200] [Batch 25/235] [D loss: -0.313331] [G loss: -0.208409]\n",
      "[Epoch 27/200] [Batch 30/235] [D loss: -0.310137] [G loss: -0.150202]\n",
      "[Epoch 27/200] [Batch 35/235] [D loss: -0.210439] [G loss: 0.016804]\n",
      "[Epoch 27/200] [Batch 40/235] [D loss: -0.285115] [G loss: -0.263760]\n",
      "[Epoch 27/200] [Batch 45/235] [D loss: -0.187121] [G loss: -0.043191]\n",
      "[Epoch 27/200] [Batch 50/235] [D loss: -0.229754] [G loss: -0.068665]\n",
      "[Epoch 27/200] [Batch 55/235] [D loss: -0.241861] [G loss: -0.168713]\n",
      "[Epoch 27/200] [Batch 60/235] [D loss: -0.213030] [G loss: -0.138010]\n",
      "[Epoch 27/200] [Batch 65/235] [D loss: -0.282528] [G loss: -0.203701]\n",
      "[Epoch 27/200] [Batch 70/235] [D loss: -0.168164] [G loss: -0.247520]\n",
      "[Epoch 27/200] [Batch 75/235] [D loss: -0.232349] [G loss: -0.397344]\n",
      "[Epoch 27/200] [Batch 80/235] [D loss: -0.254603] [G loss: -0.580373]\n",
      "[Epoch 27/200] [Batch 85/235] [D loss: -0.274350] [G loss: -0.440351]\n",
      "[Epoch 27/200] [Batch 90/235] [D loss: -0.207979] [G loss: -0.019445]\n",
      "[Epoch 27/200] [Batch 95/235] [D loss: -0.176848] [G loss: -0.137212]\n",
      "[Epoch 27/200] [Batch 100/235] [D loss: -0.193792] [G loss: -0.090904]\n",
      "[Epoch 27/200] [Batch 105/235] [D loss: -0.292049] [G loss: -0.312946]\n",
      "[Epoch 27/200] [Batch 110/235] [D loss: -0.262688] [G loss: -0.413686]\n",
      "[Epoch 27/200] [Batch 115/235] [D loss: -0.209972] [G loss: -0.285876]\n",
      "[Epoch 27/200] [Batch 120/235] [D loss: -0.200512] [G loss: -0.020539]\n",
      "[Epoch 27/200] [Batch 125/235] [D loss: -0.323927] [G loss: -0.651906]\n",
      "[Epoch 27/200] [Batch 130/235] [D loss: -0.285852] [G loss: -0.118308]\n",
      "[Epoch 27/200] [Batch 135/235] [D loss: -0.207829] [G loss: 0.219168]\n",
      "[Epoch 27/200] [Batch 140/235] [D loss: -0.203023] [G loss: 0.188807]\n",
      "[Epoch 27/200] [Batch 145/235] [D loss: -0.180398] [G loss: 0.255943]\n",
      "[Epoch 27/200] [Batch 150/235] [D loss: -0.195917] [G loss: 0.086897]\n",
      "[Epoch 27/200] [Batch 155/235] [D loss: -0.197351] [G loss: -0.113851]\n",
      "[Epoch 27/200] [Batch 160/235] [D loss: -0.225177] [G loss: -0.141165]\n",
      "[Epoch 27/200] [Batch 165/235] [D loss: -0.264088] [G loss: -0.655407]\n",
      "[Epoch 27/200] [Batch 170/235] [D loss: -0.230605] [G loss: -0.522215]\n",
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      "[Epoch 27/200] [Batch 180/235] [D loss: -0.224610] [G loss: -0.213312]\n",
      "[Epoch 27/200] [Batch 185/235] [D loss: -0.180552] [G loss: -0.051478]\n",
      "[Epoch 27/200] [Batch 190/235] [D loss: -0.212996] [G loss: -0.126586]\n",
      "[Epoch 27/200] [Batch 195/235] [D loss: -0.185227] [G loss: -0.566300]\n",
      "[Epoch 27/200] [Batch 200/235] [D loss: -0.318532] [G loss: -0.115856]\n",
      "[Epoch 27/200] [Batch 205/235] [D loss: -0.212974] [G loss: -0.245568]\n",
      "[Epoch 27/200] [Batch 210/235] [D loss: -0.171214] [G loss: -0.144092]\n",
      "[Epoch 27/200] [Batch 215/235] [D loss: -0.180073] [G loss: -0.180665]\n",
      "[Epoch 27/200] [Batch 220/235] [D loss: -0.225572] [G loss: -0.484565]\n",
      "[Epoch 27/200] [Batch 225/235] [D loss: -0.177765] [G loss: -0.455096]\n",
      "[Epoch 27/200] [Batch 230/235] [D loss: -0.168174] [G loss: -0.294173]\n",
      "[Epoch 28/200] [Batch 0/235] [D loss: -0.180283] [G loss: -0.221807]\n",
      "[Epoch 28/200] [Batch 5/235] [D loss: -0.169311] [G loss: -0.466906]\n",
      "[Epoch 28/200] [Batch 10/235] [D loss: -0.169326] [G loss: 0.001825]\n",
      "[Epoch 28/200] [Batch 15/235] [D loss: -0.166074] [G loss: -0.360064]\n",
      "[Epoch 28/200] [Batch 20/235] [D loss: -0.220430] [G loss: -0.197882]\n",
      "[Epoch 28/200] [Batch 25/235] [D loss: -0.160711] [G loss: -0.563840]\n",
      "[Epoch 28/200] [Batch 30/235] [D loss: -0.300335] [G loss: -0.380006]\n",
      "[Epoch 28/200] [Batch 35/235] [D loss: -0.165592] [G loss: -0.181250]\n",
      "[Epoch 28/200] [Batch 40/235] [D loss: -0.204828] [G loss: -0.159947]\n",
      "[Epoch 28/200] [Batch 45/235] [D loss: -0.177862] [G loss: -0.104693]\n",
      "[Epoch 28/200] [Batch 50/235] [D loss: -0.157209] [G loss: 0.025263]\n",
      "[Epoch 28/200] [Batch 55/235] [D loss: -0.184926] [G loss: -0.349857]\n",
      "[Epoch 28/200] [Batch 60/235] [D loss: -0.179760] [G loss: -0.231644]\n",
      "[Epoch 28/200] [Batch 65/235] [D loss: -0.217714] [G loss: -0.313105]\n",
      "[Epoch 28/200] [Batch 70/235] [D loss: -0.249554] [G loss: -0.528781]\n",
      "[Epoch 28/200] [Batch 75/235] [D loss: -0.112367] [G loss: -0.304020]\n",
      "[Epoch 28/200] [Batch 80/235] [D loss: -0.236950] [G loss: 0.203428]\n",
      "[Epoch 28/200] [Batch 85/235] [D loss: -0.208497] [G loss: 0.078490]\n",
      "[Epoch 28/200] [Batch 90/235] [D loss: -0.176082] [G loss: -0.098304]\n",
      "[Epoch 28/200] [Batch 95/235] [D loss: -0.165407] [G loss: 0.092009]\n",
      "[Epoch 28/200] [Batch 100/235] [D loss: -0.168859] [G loss: 0.128100]\n",
      "[Epoch 28/200] [Batch 105/235] [D loss: -0.179784] [G loss: -0.104334]\n",
      "[Epoch 28/200] [Batch 110/235] [D loss: -0.164760] [G loss: -0.169757]\n",
      "[Epoch 28/200] [Batch 115/235] [D loss: -0.207069] [G loss: -0.511165]\n",
      "[Epoch 28/200] [Batch 120/235] [D loss: -0.182402] [G loss: -0.094100]\n",
      "[Epoch 28/200] [Batch 125/235] [D loss: -0.232731] [G loss: -0.226483]\n",
      "[Epoch 28/200] [Batch 130/235] [D loss: -0.167660] [G loss: -0.187792]\n",
      "[Epoch 28/200] [Batch 135/235] [D loss: -0.189096] [G loss: -0.235797]\n",
      "[Epoch 28/200] [Batch 140/235] [D loss: -0.170425] [G loss: -0.478335]\n",
      "[Epoch 28/200] [Batch 145/235] [D loss: -0.191179] [G loss: -0.244100]\n",
      "[Epoch 28/200] [Batch 150/235] [D loss: -0.189906] [G loss: -0.647440]\n",
      "[Epoch 28/200] [Batch 155/235] [D loss: -0.159890] [G loss: -0.152208]\n",
      "[Epoch 28/200] [Batch 160/235] [D loss: -0.147878] [G loss: -0.116397]\n",
      "[Epoch 28/200] [Batch 165/235] [D loss: -0.185550] [G loss: -0.350610]\n",
      "[Epoch 28/200] [Batch 170/235] [D loss: -0.170437] [G loss: 0.092100]\n",
      "[Epoch 28/200] [Batch 175/235] [D loss: -0.240605] [G loss: -0.655540]\n",
      "[Epoch 28/200] [Batch 180/235] [D loss: -0.362968] [G loss: -0.271073]\n",
      "[Epoch 28/200] [Batch 185/235] [D loss: -0.153686] [G loss: 0.204971]\n",
      "[Epoch 28/200] [Batch 190/235] [D loss: -0.157625] [G loss: 0.198442]\n",
      "[Epoch 28/200] [Batch 195/235] [D loss: -0.168480] [G loss: -0.083182]\n",
      "[Epoch 28/200] [Batch 200/235] [D loss: -0.191961] [G loss: -0.406890]\n",
      "[Epoch 28/200] [Batch 205/235] [D loss: -0.173612] [G loss: 0.327558]\n",
      "[Epoch 28/200] [Batch 210/235] [D loss: -0.154451] [G loss: -0.129815]\n",
      "[Epoch 28/200] [Batch 215/235] [D loss: -0.166000] [G loss: -0.374639]\n",
      "[Epoch 28/200] [Batch 220/235] [D loss: -0.171016] [G loss: -0.295227]\n",
      "[Epoch 28/200] [Batch 225/235] [D loss: -0.153755] [G loss: 0.100561]\n",
      "[Epoch 28/200] [Batch 230/235] [D loss: -0.215266] [G loss: -0.454716]\n",
      "[Epoch 29/200] [Batch 0/235] [D loss: -0.224351] [G loss: -0.512475]\n",
      "[Epoch 29/200] [Batch 5/235] [D loss: -0.156064] [G loss: -0.192917]\n",
      "[Epoch 29/200] [Batch 10/235] [D loss: -0.238432] [G loss: 0.316348]\n",
      "[Epoch 29/200] [Batch 15/235] [D loss: -0.173304] [G loss: 0.324770]\n",
      "[Epoch 29/200] [Batch 20/235] [D loss: -0.166224] [G loss: -0.021711]\n",
      "[Epoch 29/200] [Batch 25/235] [D loss: -0.194624] [G loss: -0.610299]\n",
      "[Epoch 29/200] [Batch 30/235] [D loss: -0.222347] [G loss: -1.262509]\n",
      "[Epoch 29/200] [Batch 35/235] [D loss: -0.067710] [G loss: -0.232901]\n",
      "[Epoch 29/200] [Batch 40/235] [D loss: -0.154877] [G loss: 1.034901]\n",
      "[Epoch 29/200] [Batch 45/235] [D loss: -0.180999] [G loss: 1.377731]\n",
      "[Epoch 29/200] [Batch 50/235] [D loss: -0.116746] [G loss: 0.790477]\n",
      "[Epoch 29/200] [Batch 55/235] [D loss: -0.141294] [G loss: 0.049234]\n",
      "[Epoch 29/200] [Batch 60/235] [D loss: -0.173852] [G loss: -0.249104]\n",
      "[Epoch 29/200] [Batch 65/235] [D loss: -0.174788] [G loss: -0.189538]\n",
      "[Epoch 29/200] [Batch 70/235] [D loss: -0.187938] [G loss: -0.765709]\n",
      "[Epoch 29/200] [Batch 75/235] [D loss: -0.169199] [G loss: -0.658402]\n",
      "[Epoch 29/200] [Batch 80/235] [D loss: -0.154306] [G loss: -0.465489]\n",
      "[Epoch 29/200] [Batch 85/235] [D loss: -0.151979] [G loss: -0.121080]\n",
      "[Epoch 29/200] [Batch 90/235] [D loss: -0.217619] [G loss: -0.482697]\n",
      "[Epoch 29/200] [Batch 95/235] [D loss: -0.194203] [G loss: -0.900087]\n",
      "[Epoch 29/200] [Batch 100/235] [D loss: -0.161834] [G loss: -0.598420]\n",
      "[Epoch 29/200] [Batch 105/235] [D loss: -0.115377] [G loss: -0.314083]\n",
      "[Epoch 29/200] [Batch 110/235] [D loss: -0.155216] [G loss: -0.740385]\n",
      "[Epoch 29/200] [Batch 115/235] [D loss: -0.125114] [G loss: -0.866051]\n",
      "[Epoch 29/200] [Batch 120/235] [D loss: -0.166598] [G loss: -1.085205]\n",
      "[Epoch 29/200] [Batch 125/235] [D loss: -0.136984] [G loss: -0.648543]\n",
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      "[Epoch 30/200] [Batch 0/235] [D loss: -0.139073] [G loss: 0.065743]\n",
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      "[Epoch 31/200] [Batch 0/235] [D loss: -0.142971] [G loss: -0.292671]\n",
      "[Epoch 31/200] [Batch 5/235] [D loss: -0.210274] [G loss: -0.374421]\n",
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      "[Epoch 31/200] [Batch 85/235] [D loss: -0.071946] [G loss: -0.010002]\n",
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      "[Epoch 31/200] [Batch 95/235] [D loss: -0.172963] [G loss: 0.157457]\n",
      "[Epoch 31/200] [Batch 100/235] [D loss: -0.167370] [G loss: 0.450665]\n",
      "[Epoch 31/200] [Batch 105/235] [D loss: -0.223757] [G loss: 0.120247]\n",
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      "[Epoch 31/200] [Batch 115/235] [D loss: -0.146575] [G loss: -0.002633]\n",
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      "[Epoch 31/200] [Batch 125/235] [D loss: -0.181866] [G loss: -0.158243]\n",
      "[Epoch 31/200] [Batch 130/235] [D loss: -0.121958] [G loss: -0.544270]\n",
      "[Epoch 31/200] [Batch 135/235] [D loss: -0.156106] [G loss: -0.254611]\n",
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      "[Epoch 31/200] [Batch 145/235] [D loss: -0.208265] [G loss: -1.023903]\n",
      "[Epoch 31/200] [Batch 150/235] [D loss: -0.138493] [G loss: -0.317858]\n",
      "[Epoch 31/200] [Batch 155/235] [D loss: -0.156115] [G loss: 0.040444]\n",
      "[Epoch 31/200] [Batch 160/235] [D loss: -0.129546] [G loss: -0.016267]\n",
      "[Epoch 31/200] [Batch 165/235] [D loss: -0.170798] [G loss: -0.432363]\n",
      "[Epoch 31/200] [Batch 170/235] [D loss: -0.191651] [G loss: -0.095103]\n",
      "[Epoch 31/200] [Batch 175/235] [D loss: -0.111989] [G loss: -0.465665]\n",
      "[Epoch 31/200] [Batch 180/235] [D loss: -0.142531] [G loss: -0.750209]\n",
      "[Epoch 31/200] [Batch 185/235] [D loss: -0.167613] [G loss: -0.480343]\n",
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      "[Epoch 31/200] [Batch 195/235] [D loss: -0.086699] [G loss: -0.511861]\n",
      "[Epoch 31/200] [Batch 200/235] [D loss: -0.184508] [G loss: -0.371149]\n",
      "[Epoch 31/200] [Batch 205/235] [D loss: -0.292333] [G loss: -0.176643]\n",
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      "[Epoch 31/200] [Batch 215/235] [D loss: -0.150449] [G loss: -0.059238]\n",
      "[Epoch 31/200] [Batch 220/235] [D loss: -0.154151] [G loss: 0.031458]\n",
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      "[Epoch 32/200] [Batch 0/235] [D loss: -0.209555] [G loss: -0.171831]\n",
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      "[Epoch 32/200] [Batch 15/235] [D loss: -0.145756] [G loss: -0.330536]\n",
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      "[Epoch 32/200] [Batch 60/235] [D loss: -0.191462] [G loss: -0.543495]\n",
      "[Epoch 32/200] [Batch 65/235] [D loss: -0.145289] [G loss: -0.340014]\n",
      "[Epoch 32/200] [Batch 70/235] [D loss: -0.095390] [G loss: -0.199180]\n",
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      "[Epoch 32/200] [Batch 85/235] [D loss: -0.165778] [G loss: -0.453176]\n",
      "[Epoch 32/200] [Batch 90/235] [D loss: -0.210575] [G loss: -0.541401]\n",
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      "[Epoch 32/200] [Batch 100/235] [D loss: -0.162798] [G loss: 0.057790]\n",
      "[Epoch 32/200] [Batch 105/235] [D loss: -0.150868] [G loss: -0.262738]\n",
      "[Epoch 32/200] [Batch 110/235] [D loss: -0.220631] [G loss: -0.463219]\n",
      "[Epoch 32/200] [Batch 115/235] [D loss: -0.192031] [G loss: -0.352414]\n",
      "[Epoch 32/200] [Batch 120/235] [D loss: -0.149024] [G loss: -0.339032]\n",
      "[Epoch 32/200] [Batch 125/235] [D loss: -0.108021] [G loss: -0.068756]\n",
      "[Epoch 32/200] [Batch 130/235] [D loss: -0.126688] [G loss: -0.302698]\n",
      "[Epoch 32/200] [Batch 135/235] [D loss: -0.244954] [G loss: -0.664129]\n",
      "[Epoch 32/200] [Batch 140/235] [D loss: -0.163803] [G loss: -0.506528]\n",
      "[Epoch 32/200] [Batch 145/235] [D loss: -0.155136] [G loss: -0.187708]\n",
      "[Epoch 32/200] [Batch 150/235] [D loss: -0.162451] [G loss: 0.140801]\n",
      "[Epoch 32/200] [Batch 155/235] [D loss: -0.178507] [G loss: -0.721675]\n",
      "[Epoch 32/200] [Batch 160/235] [D loss: -0.226053] [G loss: -0.543940]\n",
      "[Epoch 32/200] [Batch 165/235] [D loss: -0.162853] [G loss: 0.014056]\n",
      "[Epoch 32/200] [Batch 170/235] [D loss: -0.133113] [G loss: 0.017941]\n",
      "[Epoch 32/200] [Batch 175/235] [D loss: -0.176143] [G loss: 0.138603]\n",
      "[Epoch 32/200] [Batch 180/235] [D loss: -0.167563] [G loss: -0.480511]\n",
      "[Epoch 32/200] [Batch 185/235] [D loss: -0.200577] [G loss: -0.449068]\n",
      "[Epoch 32/200] [Batch 190/235] [D loss: -0.138664] [G loss: -0.279571]\n",
      "[Epoch 32/200] [Batch 195/235] [D loss: -0.167470] [G loss: -0.025083]\n",
      "[Epoch 32/200] [Batch 200/235] [D loss: -0.152791] [G loss: -0.144879]\n",
      "[Epoch 32/200] [Batch 205/235] [D loss: -0.207580] [G loss: -0.844174]\n",
      "[Epoch 32/200] [Batch 210/235] [D loss: -0.164533] [G loss: -0.081363]\n",
      "[Epoch 32/200] [Batch 215/235] [D loss: -0.074771] [G loss: -0.020922]\n",
      "[Epoch 32/200] [Batch 220/235] [D loss: -0.177192] [G loss: -0.146119]\n",
      "[Epoch 32/200] [Batch 225/235] [D loss: -0.129653] [G loss: -0.239853]\n",
      "[Epoch 32/200] [Batch 230/235] [D loss: -0.160466] [G loss: -0.542642]\n",
      "[Epoch 33/200] [Batch 0/235] [D loss: -0.161989] [G loss: -0.223253]\n",
      "[Epoch 33/200] [Batch 5/235] [D loss: -0.144809] [G loss: 0.020379]\n",
      "[Epoch 33/200] [Batch 10/235] [D loss: -0.180754] [G loss: -0.425165]\n",
      "[Epoch 33/200] [Batch 15/235] [D loss: -0.262275] [G loss: -0.351684]\n",
      "[Epoch 33/200] [Batch 20/235] [D loss: -0.155357] [G loss: 0.012094]\n",
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      "[Epoch 33/200] [Batch 30/235] [D loss: -0.186043] [G loss: -0.139800]\n",
      "[Epoch 33/200] [Batch 35/235] [D loss: -0.167596] [G loss: 0.086070]\n",
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      "[Epoch 33/200] [Batch 45/235] [D loss: -0.205241] [G loss: -0.563307]\n",
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      "[Epoch 33/200] [Batch 60/235] [D loss: -0.102798] [G loss: -0.319419]\n",
      "[Epoch 33/200] [Batch 65/235] [D loss: -0.164777] [G loss: -0.416628]\n",
      "[Epoch 33/200] [Batch 70/235] [D loss: -0.188925] [G loss: -0.197554]\n",
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      "[Epoch 33/200] [Batch 80/235] [D loss: -0.228725] [G loss: -0.199586]\n",
      "[Epoch 33/200] [Batch 85/235] [D loss: -0.164706] [G loss: -0.371208]\n",
      "[Epoch 33/200] [Batch 90/235] [D loss: -0.146686] [G loss: -0.006575]\n",
      "[Epoch 33/200] [Batch 95/235] [D loss: -0.165341] [G loss: -0.248899]\n",
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      "[Epoch 33/200] [Batch 140/235] [D loss: -0.206133] [G loss: -0.531457]\n",
      "[Epoch 33/200] [Batch 145/235] [D loss: -0.088697] [G loss: -0.285638]\n",
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      "[Epoch 33/200] [Batch 155/235] [D loss: -0.137130] [G loss: 0.288823]\n",
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      "[Epoch 33/200] [Batch 170/235] [D loss: -0.218185] [G loss: 0.265602]\n",
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      "[Epoch 33/200] [Batch 180/235] [D loss: -0.172025] [G loss: -0.155850]\n",
      "[Epoch 33/200] [Batch 185/235] [D loss: -0.115615] [G loss: 0.220048]\n",
      "[Epoch 33/200] [Batch 190/235] [D loss: -0.185729] [G loss: 0.098672]\n",
      "[Epoch 33/200] [Batch 195/235] [D loss: -0.181581] [G loss: 0.045167]\n",
      "[Epoch 33/200] [Batch 200/235] [D loss: -0.223332] [G loss: 0.109515]\n",
      "[Epoch 33/200] [Batch 205/235] [D loss: -0.128742] [G loss: 0.087794]\n",
      "[Epoch 33/200] [Batch 210/235] [D loss: -0.267107] [G loss: -0.638984]\n",
      "[Epoch 33/200] [Batch 215/235] [D loss: -0.151494] [G loss: -0.099145]\n",
      "[Epoch 33/200] [Batch 220/235] [D loss: -0.114715] [G loss: -0.140604]\n",
      "[Epoch 33/200] [Batch 225/235] [D loss: -0.151488] [G loss: -0.125602]\n",
      "[Epoch 33/200] [Batch 230/235] [D loss: -0.185447] [G loss: -0.422641]\n",
      "[Epoch 34/200] [Batch 0/235] [D loss: -0.149957] [G loss: -0.116426]\n",
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      "[Epoch 35/200] [Batch 0/235] [D loss: -0.115698] [G loss: -0.998369]\n",
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      "[Epoch 36/200] [Batch 0/235] [D loss: -0.105329] [G loss: -0.096917]\n",
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      "[Epoch 37/200] [Batch 0/235] [D loss: -0.170756] [G loss: 1.032681]\n",
      "[Epoch 37/200] [Batch 5/235] [D loss: -0.083951] [G loss: -0.197011]\n",
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      "[Epoch 37/200] [Batch 50/235] [D loss: -0.138512] [G loss: -0.422771]\n",
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      "[Epoch 37/200] [Batch 70/235] [D loss: -0.125865] [G loss: -0.558912]\n",
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      "[Epoch 37/200] [Batch 80/235] [D loss: -0.116735] [G loss: -0.463724]\n",
      "[Epoch 37/200] [Batch 85/235] [D loss: -0.141994] [G loss: -0.285755]\n",
      "[Epoch 37/200] [Batch 90/235] [D loss: -0.115671] [G loss: -0.436546]\n",
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      "[Epoch 37/200] [Batch 100/235] [D loss: -0.131781] [G loss: 0.126601]\n",
      "[Epoch 37/200] [Batch 105/235] [D loss: -0.111382] [G loss: -0.135378]\n",
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      "[Epoch 37/200] [Batch 115/235] [D loss: -0.114046] [G loss: -0.139159]\n",
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      "[Epoch 37/200] [Batch 125/235] [D loss: -0.168730] [G loss: -0.139786]\n",
      "[Epoch 37/200] [Batch 130/235] [D loss: -0.123624] [G loss: -0.175946]\n",
      "[Epoch 37/200] [Batch 135/235] [D loss: -0.101229] [G loss: -0.258758]\n",
      "[Epoch 37/200] [Batch 140/235] [D loss: -0.131920] [G loss: -0.057639]\n",
      "[Epoch 37/200] [Batch 145/235] [D loss: -0.179269] [G loss: -0.521657]\n",
      "[Epoch 37/200] [Batch 150/235] [D loss: -0.196754] [G loss: -0.427821]\n",
      "[Epoch 37/200] [Batch 155/235] [D loss: -0.227658] [G loss: -0.994676]\n",
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      "[Epoch 37/200] [Batch 165/235] [D loss: -0.184169] [G loss: -0.063709]\n",
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      "[Epoch 37/200] [Batch 180/235] [D loss: -0.104802] [G loss: -0.086928]\n",
      "[Epoch 37/200] [Batch 185/235] [D loss: -0.129847] [G loss: -0.244043]\n",
      "[Epoch 37/200] [Batch 190/235] [D loss: -0.167505] [G loss: -1.073337]\n",
      "[Epoch 37/200] [Batch 195/235] [D loss: -0.078734] [G loss: 0.066375]\n",
      "[Epoch 37/200] [Batch 200/235] [D loss: -0.201123] [G loss: -0.386703]\n",
      "[Epoch 37/200] [Batch 205/235] [D loss: -0.120831] [G loss: -0.119986]\n",
      "[Epoch 37/200] [Batch 210/235] [D loss: -0.160907] [G loss: -0.384339]\n",
      "[Epoch 37/200] [Batch 215/235] [D loss: -0.170429] [G loss: -0.473780]\n",
      "[Epoch 37/200] [Batch 220/235] [D loss: -0.140406] [G loss: -0.523438]\n",
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      "[Epoch 37/200] [Batch 230/235] [D loss: -0.141047] [G loss: -0.547387]\n",
      "[Epoch 38/200] [Batch 0/235] [D loss: -0.122009] [G loss: -0.481030]\n",
      "[Epoch 38/200] [Batch 5/235] [D loss: -0.115848] [G loss: -0.705555]\n",
      "[Epoch 38/200] [Batch 10/235] [D loss: -0.107757] [G loss: -0.389594]\n",
      "[Epoch 38/200] [Batch 15/235] [D loss: -0.152207] [G loss: -0.735268]\n",
      "[Epoch 38/200] [Batch 20/235] [D loss: -0.194485] [G loss: -0.924725]\n",
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      "[Epoch 38/200] [Batch 30/235] [D loss: -0.123816] [G loss: -0.302636]\n",
      "[Epoch 38/200] [Batch 35/235] [D loss: -0.135896] [G loss: -0.356683]\n",
      "[Epoch 38/200] [Batch 40/235] [D loss: -0.181685] [G loss: -0.871217]\n",
      "[Epoch 38/200] [Batch 45/235] [D loss: -0.205868] [G loss: -0.648163]\n",
      "[Epoch 38/200] [Batch 50/235] [D loss: -0.154954] [G loss: -0.299951]\n",
      "[Epoch 38/200] [Batch 55/235] [D loss: -0.097483] [G loss: 0.061132]\n",
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      "[Epoch 38/200] [Batch 65/235] [D loss: -0.159748] [G loss: -0.444199]\n",
      "[Epoch 38/200] [Batch 70/235] [D loss: -0.233458] [G loss: -1.045341]\n",
      "[Epoch 38/200] [Batch 75/235] [D loss: -0.060949] [G loss: -0.418461]\n",
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      "[Epoch 38/200] [Batch 85/235] [D loss: -0.122726] [G loss: 1.188950]\n",
      "[Epoch 38/200] [Batch 90/235] [D loss: -0.064011] [G loss: 0.210854]\n",
      "[Epoch 38/200] [Batch 95/235] [D loss: -0.139316] [G loss: -0.649607]\n",
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      "[Epoch 39/200] [Batch 0/235] [D loss: -0.103018] [G loss: -0.425866]\n",
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      "[Epoch 40/200] [Batch 0/235] [D loss: -0.083316] [G loss: -0.185829]\n",
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      "[Epoch 40/200] [Batch 85/235] [D loss: -0.091386] [G loss: -0.744033]\n",
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      "[Epoch 40/200] [Batch 100/235] [D loss: -0.103320] [G loss: -0.367892]\n",
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      "[Epoch 40/200] [Batch 135/235] [D loss: -0.104357] [G loss: -0.764561]\n",
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      "[Epoch 40/200] [Batch 150/235] [D loss: -0.096366] [G loss: -0.235971]\n",
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      "[Epoch 40/200] [Batch 165/235] [D loss: -0.108842] [G loss: -0.399597]\n",
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      "[Epoch 40/200] [Batch 200/235] [D loss: -0.110755] [G loss: 1.195611]\n",
      "[Epoch 40/200] [Batch 205/235] [D loss: -0.129542] [G loss: 0.786642]\n",
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      "[Epoch 41/200] [Batch 0/235] [D loss: -0.096986] [G loss: 0.333396]\n",
      "[Epoch 41/200] [Batch 5/235] [D loss: -0.089764] [G loss: 0.236213]\n",
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      "[Epoch 41/200] [Batch 40/235] [D loss: -0.133759] [G loss: 0.322586]\n",
      "[Epoch 41/200] [Batch 45/235] [D loss: -0.138438] [G loss: 0.505542]\n",
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      "[Epoch 41/200] [Batch 70/235] [D loss: -0.101032] [G loss: 0.298265]\n",
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      "[Epoch 41/200] [Batch 95/235] [D loss: -0.138043] [G loss: -0.464797]\n",
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      "[Epoch 41/200] [Batch 120/235] [D loss: -0.153098] [G loss: -1.253048]\n",
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      "[Epoch 41/200] [Batch 165/235] [D loss: -0.120334] [G loss: -0.712319]\n",
      "[Epoch 41/200] [Batch 170/235] [D loss: -0.117642] [G loss: -1.004879]\n",
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      "[Epoch 41/200] [Batch 180/235] [D loss: -0.107564] [G loss: 0.244080]\n",
      "[Epoch 41/200] [Batch 185/235] [D loss: -0.130303] [G loss: 0.681757]\n",
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      "[Epoch 41/200] [Batch 195/235] [D loss: -0.158894] [G loss: -0.712898]\n",
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      "[Epoch 41/200] [Batch 205/235] [D loss: -0.100308] [G loss: -0.202911]\n",
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      "[Epoch 42/200] [Batch 0/235] [D loss: -0.101987] [G loss: -0.133936]\n",
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      "[Epoch 42/200] [Batch 45/235] [D loss: -0.113792] [G loss: -0.827597]\n",
      "[Epoch 42/200] [Batch 50/235] [D loss: -0.134285] [G loss: -0.874275]\n",
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      "[Epoch 42/200] [Batch 65/235] [D loss: -0.130465] [G loss: 0.194306]\n",
      "[Epoch 42/200] [Batch 70/235] [D loss: -0.113177] [G loss: 0.021239]\n",
      "[Epoch 42/200] [Batch 75/235] [D loss: -0.141079] [G loss: -0.153899]\n",
      "[Epoch 42/200] [Batch 80/235] [D loss: -0.124590] [G loss: -0.186180]\n",
      "[Epoch 42/200] [Batch 85/235] [D loss: -0.108621] [G loss: -0.478912]\n",
      "[Epoch 42/200] [Batch 90/235] [D loss: -0.119402] [G loss: -0.602996]\n",
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      "[Epoch 42/200] [Batch 100/235] [D loss: -0.159475] [G loss: -0.071710]\n",
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      "[Epoch 42/200] [Batch 120/235] [D loss: -0.133340] [G loss: -0.532573]\n",
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      "[Epoch 42/200] [Batch 135/235] [D loss: -0.116894] [G loss: -0.366173]\n",
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      "[Epoch 42/200] [Batch 170/235] [D loss: -0.115328] [G loss: -0.671431]\n",
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      "[Epoch 45/200] [Batch 0/235] [D loss: -0.059143] [G loss: 0.207357]\n",
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      "[Epoch 45/200] [Batch 40/235] [D loss: -0.121586] [G loss: -0.858599]\n",
      "[Epoch 45/200] [Batch 45/235] [D loss: -0.099932] [G loss: -0.466962]\n",
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      "[Epoch 46/200] [Batch 0/235] [D loss: -0.113259] [G loss: -0.181412]\n",
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      "[Epoch 46/200] [Batch 40/235] [D loss: -0.147918] [G loss: 0.786363]\n",
      "[Epoch 46/200] [Batch 45/235] [D loss: -0.104910] [G loss: -0.108102]\n",
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      "[Epoch 46/200] [Batch 65/235] [D loss: -0.107120] [G loss: 1.322047]\n",
      "[Epoch 46/200] [Batch 70/235] [D loss: -0.112546] [G loss: 0.579346]\n",
      "[Epoch 46/200] [Batch 75/235] [D loss: -0.104003] [G loss: -0.442221]\n",
      "[Epoch 46/200] [Batch 80/235] [D loss: -0.094033] [G loss: -0.376744]\n",
      "[Epoch 46/200] [Batch 85/235] [D loss: -0.144716] [G loss: -0.136831]\n",
      "[Epoch 46/200] [Batch 90/235] [D loss: -0.073049] [G loss: 0.095797]\n",
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      "[Epoch 46/200] [Batch 100/235] [D loss: -0.106537] [G loss: -0.382591]\n",
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      "[Epoch 46/200] [Batch 125/235] [D loss: -0.113911] [G loss: 0.100304]\n",
      "[Epoch 46/200] [Batch 130/235] [D loss: -0.133186] [G loss: -0.077969]\n",
      "[Epoch 46/200] [Batch 135/235] [D loss: -0.089858] [G loss: -0.145224]\n",
      "[Epoch 46/200] [Batch 140/235] [D loss: -0.115401] [G loss: -0.277730]\n",
      "[Epoch 46/200] [Batch 145/235] [D loss: -0.124749] [G loss: -0.526752]\n",
      "[Epoch 46/200] [Batch 150/235] [D loss: -0.104212] [G loss: -0.579491]\n",
      "[Epoch 46/200] [Batch 155/235] [D loss: -0.099979] [G loss: -0.527458]\n",
      "[Epoch 46/200] [Batch 160/235] [D loss: -0.130956] [G loss: -0.246083]\n",
      "[Epoch 46/200] [Batch 165/235] [D loss: -0.077291] [G loss: -0.129337]\n",
      "[Epoch 46/200] [Batch 170/235] [D loss: -0.091950] [G loss: -0.068455]\n",
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      "[Epoch 46/200] [Batch 180/235] [D loss: -0.074551] [G loss: 0.076383]\n",
      "[Epoch 46/200] [Batch 185/235] [D loss: -0.109317] [G loss: -0.342437]\n",
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      "[Epoch 46/200] [Batch 200/235] [D loss: -0.113622] [G loss: -0.201282]\n",
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      "[Epoch 47/200] [Batch 0/235] [D loss: -0.098096] [G loss: -0.119250]\n",
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      "[Epoch 47/200] [Batch 15/235] [D loss: -0.099991] [G loss: -0.469699]\n",
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      "[Epoch 47/200] [Batch 40/235] [D loss: -0.108191] [G loss: -0.052195]\n",
      "[Epoch 47/200] [Batch 45/235] [D loss: -0.084627] [G loss: 0.030905]\n",
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      "[Epoch 47/200] [Batch 60/235] [D loss: -0.084447] [G loss: -0.108972]\n",
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      "[Epoch 48/200] [Batch 0/235] [D loss: -0.103363] [G loss: 0.101661]\n",
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      "[Epoch 49/200] [Batch 0/235] [D loss: -0.089739] [G loss: 0.217514]\n",
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      "[Epoch 50/200] [Batch 0/235] [D loss: -0.076314] [G loss: -0.627381]\n",
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      "[Epoch 50/200] [Batch 50/235] [D loss: -0.076319] [G loss: 0.375891]\n",
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      "[Epoch 50/200] [Batch 85/235] [D loss: -0.120188] [G loss: 1.040922]\n",
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      "[Epoch 50/200] [Batch 95/235] [D loss: -0.127957] [G loss: 0.848138]\n",
      "[Epoch 50/200] [Batch 100/235] [D loss: -0.088122] [G loss: -0.432280]\n",
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      "[Epoch 50/200] [Batch 120/235] [D loss: -0.139560] [G loss: 1.253948]\n",
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      "[Epoch 50/200] [Batch 135/235] [D loss: -0.096243] [G loss: 0.099409]\n",
      "[Epoch 50/200] [Batch 140/235] [D loss: -0.107186] [G loss: -0.210159]\n",
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      "[Epoch 50/200] [Batch 150/235] [D loss: -0.059139] [G loss: -0.247802]\n",
      "[Epoch 50/200] [Batch 155/235] [D loss: -0.103003] [G loss: -0.334061]\n",
      "[Epoch 50/200] [Batch 160/235] [D loss: -0.090962] [G loss: 0.282492]\n",
      "[Epoch 50/200] [Batch 165/235] [D loss: -0.099295] [G loss: 0.129560]\n",
      "[Epoch 50/200] [Batch 170/235] [D loss: -0.091899] [G loss: 0.088756]\n",
      "[Epoch 50/200] [Batch 175/235] [D loss: -0.091305] [G loss: -0.106575]\n",
      "[Epoch 50/200] [Batch 180/235] [D loss: -0.100513] [G loss: -0.324530]\n",
      "[Epoch 50/200] [Batch 185/235] [D loss: -0.120190] [G loss: -0.666848]\n",
      "[Epoch 50/200] [Batch 190/235] [D loss: -0.070731] [G loss: -0.615733]\n",
      "[Epoch 50/200] [Batch 195/235] [D loss: -0.090363] [G loss: -0.440461]\n",
      "[Epoch 50/200] [Batch 200/235] [D loss: -0.067419] [G loss: -0.241139]\n",
      "[Epoch 50/200] [Batch 205/235] [D loss: -0.082265] [G loss: -0.070091]\n",
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      "[Epoch 51/200] [Batch 0/235] [D loss: -0.062217] [G loss: -0.776107]\n",
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      "[Epoch 51/200] [Batch 85/235] [D loss: -0.081123] [G loss: -0.123977]\n",
      "[Epoch 51/200] [Batch 90/235] [D loss: -0.096114] [G loss: -0.025445]\n",
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      "[Epoch 51/200] [Batch 100/235] [D loss: -0.114116] [G loss: -0.161514]\n",
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      "[Epoch 51/200] [Batch 135/235] [D loss: -0.073794] [G loss: 0.019214]\n",
      "[Epoch 51/200] [Batch 140/235] [D loss: -0.117882] [G loss: -1.152380]\n",
      "[Epoch 51/200] [Batch 145/235] [D loss: -0.110978] [G loss: -1.329938]\n",
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      "[Epoch 51/200] [Batch 155/235] [D loss: -0.149232] [G loss: 0.364316]\n",
      "[Epoch 51/200] [Batch 160/235] [D loss: -0.053374] [G loss: 0.401711]\n",
      "[Epoch 51/200] [Batch 165/235] [D loss: -0.078899] [G loss: 0.392558]\n",
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      "[Epoch 52/200] [Batch 200/235] [D loss: -0.032981] [G loss: 0.085007]\n",
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      "[Epoch 53/200] [Batch 0/235] [D loss: -0.088938] [G loss: -0.139696]\n",
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      "[Epoch 53/200] [Batch 45/235] [D loss: -0.062791] [G loss: 0.172504]\n",
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      "[Epoch 53/200] [Batch 55/235] [D loss: -0.061507] [G loss: -0.287113]\n",
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      "[Epoch 53/200] [Batch 65/235] [D loss: -0.087581] [G loss: -0.850624]\n",
      "[Epoch 53/200] [Batch 70/235] [D loss: -0.076949] [G loss: 0.135412]\n",
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      "[Epoch 53/200] [Batch 80/235] [D loss: -0.081881] [G loss: 0.347439]\n",
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      "[Epoch 53/200] [Batch 100/235] [D loss: -0.052450] [G loss: -0.250373]\n",
      "[Epoch 53/200] [Batch 105/235] [D loss: -0.055156] [G loss: -0.087574]\n",
      "[Epoch 53/200] [Batch 110/235] [D loss: -0.117130] [G loss: 0.835579]\n",
      "[Epoch 53/200] [Batch 115/235] [D loss: -0.069448] [G loss: 0.531721]\n",
      "[Epoch 53/200] [Batch 120/235] [D loss: -0.071631] [G loss: -0.356587]\n",
      "[Epoch 53/200] [Batch 125/235] [D loss: -0.069821] [G loss: -0.797647]\n",
      "[Epoch 53/200] [Batch 130/235] [D loss: -0.061096] [G loss: -0.459618]\n",
      "[Epoch 53/200] [Batch 135/235] [D loss: -0.068928] [G loss: -0.458147]\n",
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      "[Epoch 53/200] [Batch 145/235] [D loss: -0.099390] [G loss: 0.316545]\n",
      "[Epoch 53/200] [Batch 150/235] [D loss: -0.065933] [G loss: 0.279152]\n",
      "[Epoch 53/200] [Batch 155/235] [D loss: -0.073828] [G loss: -0.139717]\n",
      "[Epoch 53/200] [Batch 160/235] [D loss: -0.087498] [G loss: -0.415554]\n",
      "[Epoch 53/200] [Batch 165/235] [D loss: -0.085300] [G loss: -0.044635]\n",
      "[Epoch 53/200] [Batch 170/235] [D loss: -0.095241] [G loss: 0.264569]\n",
      "[Epoch 53/200] [Batch 175/235] [D loss: -0.060448] [G loss: -0.096066]\n",
      "[Epoch 53/200] [Batch 180/235] [D loss: -0.064557] [G loss: -0.020751]\n",
      "[Epoch 53/200] [Batch 185/235] [D loss: -0.095563] [G loss: -0.224304]\n",
      "[Epoch 53/200] [Batch 190/235] [D loss: -0.061219] [G loss: -0.219484]\n",
      "[Epoch 53/200] [Batch 195/235] [D loss: -0.070589] [G loss: 0.217477]\n",
      "[Epoch 53/200] [Batch 200/235] [D loss: -0.069276] [G loss: -0.049257]\n",
      "[Epoch 53/200] [Batch 205/235] [D loss: -0.093590] [G loss: -0.358903]\n",
      "[Epoch 53/200] [Batch 210/235] [D loss: -0.065659] [G loss: -0.479189]\n",
      "[Epoch 53/200] [Batch 215/235] [D loss: -0.080922] [G loss: -0.150770]\n",
      "[Epoch 53/200] [Batch 220/235] [D loss: -0.072546] [G loss: -0.251733]\n",
      "[Epoch 53/200] [Batch 225/235] [D loss: -0.070717] [G loss: 0.974864]\n",
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      "[Epoch 54/200] [Batch 0/235] [D loss: -0.096915] [G loss: -0.162075]\n",
      "[Epoch 54/200] [Batch 5/235] [D loss: -0.090904] [G loss: -0.378067]\n",
      "[Epoch 54/200] [Batch 10/235] [D loss: -0.081751] [G loss: -0.001720]\n",
      "[Epoch 54/200] [Batch 15/235] [D loss: -0.074988] [G loss: 0.361494]\n",
      "[Epoch 54/200] [Batch 20/235] [D loss: -0.065186] [G loss: 0.172722]\n",
      "[Epoch 54/200] [Batch 25/235] [D loss: -0.088251] [G loss: 0.044496]\n",
      "[Epoch 54/200] [Batch 30/235] [D loss: -0.074626] [G loss: 0.111941]\n",
      "[Epoch 54/200] [Batch 35/235] [D loss: -0.065210] [G loss: 0.457877]\n",
      "[Epoch 54/200] [Batch 40/235] [D loss: -0.067198] [G loss: 0.044918]\n",
      "[Epoch 54/200] [Batch 45/235] [D loss: -0.113494] [G loss: -0.045441]\n",
      "[Epoch 54/200] [Batch 50/235] [D loss: -0.053100] [G loss: -0.344899]\n",
      "[Epoch 54/200] [Batch 55/235] [D loss: -0.084443] [G loss: -0.440430]\n",
      "[Epoch 54/200] [Batch 60/235] [D loss: -0.072461] [G loss: -0.045546]\n",
      "[Epoch 54/200] [Batch 65/235] [D loss: -0.067219] [G loss: -0.273820]\n",
      "[Epoch 54/200] [Batch 70/235] [D loss: -0.076263] [G loss: -0.293007]\n",
      "[Epoch 54/200] [Batch 75/235] [D loss: -0.090258] [G loss: -0.961700]\n",
      "[Epoch 54/200] [Batch 80/235] [D loss: -0.073509] [G loss: -0.310299]\n",
      "[Epoch 54/200] [Batch 85/235] [D loss: -0.058896] [G loss: 0.548704]\n",
      "[Epoch 54/200] [Batch 90/235] [D loss: -0.107022] [G loss: 0.952187]\n",
      "[Epoch 54/200] [Batch 95/235] [D loss: -0.057436] [G loss: -0.010496]\n",
      "[Epoch 54/200] [Batch 100/235] [D loss: -0.086968] [G loss: -0.158912]\n",
      "[Epoch 54/200] [Batch 105/235] [D loss: -0.091511] [G loss: 0.187644]\n",
      "[Epoch 54/200] [Batch 110/235] [D loss: -0.083884] [G loss: 0.079178]\n",
      "[Epoch 54/200] [Batch 115/235] [D loss: -0.075468] [G loss: -0.658999]\n",
      "[Epoch 54/200] [Batch 120/235] [D loss: -0.065176] [G loss: -0.620791]\n",
      "[Epoch 54/200] [Batch 125/235] [D loss: -0.070391] [G loss: -0.137597]\n",
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      "[Epoch 54/200] [Batch 135/235] [D loss: -0.091997] [G loss: 0.260323]\n",
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      "[Epoch 54/200] [Batch 150/235] [D loss: -0.073022] [G loss: 0.007176]\n",
      "[Epoch 54/200] [Batch 155/235] [D loss: -0.078407] [G loss: 0.220151]\n",
      "[Epoch 54/200] [Batch 160/235] [D loss: -0.060917] [G loss: 0.031759]\n",
      "[Epoch 54/200] [Batch 165/235] [D loss: -0.056859] [G loss: -0.116151]\n",
      "[Epoch 54/200] [Batch 170/235] [D loss: -0.087983] [G loss: -0.064572]\n",
      "[Epoch 54/200] [Batch 175/235] [D loss: -0.094805] [G loss: -0.358604]\n",
      "[Epoch 54/200] [Batch 180/235] [D loss: -0.046149] [G loss: -0.023252]\n",
      "[Epoch 54/200] [Batch 185/235] [D loss: -0.082527] [G loss: 0.138715]\n",
      "[Epoch 54/200] [Batch 190/235] [D loss: -0.087094] [G loss: 0.663075]\n",
      "[Epoch 54/200] [Batch 195/235] [D loss: -0.048189] [G loss: -0.166621]\n",
      "[Epoch 54/200] [Batch 200/235] [D loss: -0.080297] [G loss: -0.563229]\n",
      "[Epoch 54/200] [Batch 205/235] [D loss: -0.048870] [G loss: 0.329698]\n",
      "[Epoch 54/200] [Batch 210/235] [D loss: -0.043128] [G loss: 0.907623]\n",
      "[Epoch 54/200] [Batch 215/235] [D loss: -0.082116] [G loss: 1.642171]\n",
      "[Epoch 54/200] [Batch 220/235] [D loss: -0.046987] [G loss: 0.685733]\n",
      "[Epoch 54/200] [Batch 225/235] [D loss: -0.055560] [G loss: 0.123486]\n",
      "[Epoch 54/200] [Batch 230/235] [D loss: -0.058786] [G loss: -0.372313]\n",
      "[Epoch 55/200] [Batch 0/235] [D loss: -0.055009] [G loss: -0.842640]\n",
      "[Epoch 55/200] [Batch 5/235] [D loss: -0.057586] [G loss: -0.622984]\n",
      "[Epoch 55/200] [Batch 10/235] [D loss: -0.057492] [G loss: -0.350789]\n",
      "[Epoch 55/200] [Batch 15/235] [D loss: -0.072469] [G loss: -0.334143]\n",
      "[Epoch 55/200] [Batch 20/235] [D loss: -0.041163] [G loss: -0.531229]\n",
      "[Epoch 55/200] [Batch 25/235] [D loss: -0.050729] [G loss: -0.328315]\n",
      "[Epoch 55/200] [Batch 30/235] [D loss: -0.056399] [G loss: 0.032360]\n",
      "[Epoch 55/200] [Batch 35/235] [D loss: -0.080370] [G loss: 0.504567]\n",
      "[Epoch 55/200] [Batch 40/235] [D loss: -0.042156] [G loss: 0.694276]\n",
      "[Epoch 55/200] [Batch 45/235] [D loss: -0.049401] [G loss: 0.360960]\n",
      "[Epoch 55/200] [Batch 50/235] [D loss: -0.074538] [G loss: -0.171118]\n",
      "[Epoch 55/200] [Batch 55/235] [D loss: -0.069230] [G loss: -0.210389]\n",
      "[Epoch 55/200] [Batch 60/235] [D loss: -0.050622] [G loss: -0.316386]\n",
      "[Epoch 55/200] [Batch 65/235] [D loss: -0.069942] [G loss: -0.636427]\n",
      "[Epoch 55/200] [Batch 70/235] [D loss: -0.077171] [G loss: -0.340163]\n",
      "[Epoch 55/200] [Batch 75/235] [D loss: -0.061027] [G loss: -0.610276]\n",
      "[Epoch 55/200] [Batch 80/235] [D loss: -0.065703] [G loss: -0.162015]\n",
      "[Epoch 55/200] [Batch 85/235] [D loss: -0.053577] [G loss: 0.160762]\n",
      "[Epoch 55/200] [Batch 90/235] [D loss: -0.056080] [G loss: 0.759844]\n",
      "[Epoch 55/200] [Batch 95/235] [D loss: -0.064750] [G loss: 0.946681]\n",
      "[Epoch 55/200] [Batch 100/235] [D loss: -0.127916] [G loss: 1.148449]\n",
      "[Epoch 55/200] [Batch 105/235] [D loss: -0.051702] [G loss: -0.034098]\n",
      "[Epoch 55/200] [Batch 110/235] [D loss: -0.079412] [G loss: -1.253207]\n",
      "[Epoch 55/200] [Batch 115/235] [D loss: -0.077221] [G loss: -1.360380]\n",
      "[Epoch 55/200] [Batch 120/235] [D loss: -0.085376] [G loss: 0.051836]\n",
      "[Epoch 55/200] [Batch 125/235] [D loss: -0.065947] [G loss: 0.561876]\n",
      "[Epoch 55/200] [Batch 130/235] [D loss: -0.085744] [G loss: 0.499937]\n",
      "[Epoch 55/200] [Batch 135/235] [D loss: -0.055183] [G loss: 0.118748]\n",
      "[Epoch 55/200] [Batch 140/235] [D loss: -0.094977] [G loss: 0.112533]\n",
      "[Epoch 55/200] [Batch 145/235] [D loss: -0.084627] [G loss: 0.371888]\n",
      "[Epoch 55/200] [Batch 150/235] [D loss: -0.041822] [G loss: 0.306591]\n",
      "[Epoch 55/200] [Batch 155/235] [D loss: -0.089565] [G loss: 0.467917]\n",
      "[Epoch 55/200] [Batch 160/235] [D loss: -0.065366] [G loss: 0.097497]\n",
      "[Epoch 55/200] [Batch 165/235] [D loss: -0.071655] [G loss: -0.174572]\n",
      "[Epoch 55/200] [Batch 170/235] [D loss: -0.033041] [G loss: -0.118709]\n",
      "[Epoch 55/200] [Batch 175/235] [D loss: -0.085075] [G loss: -0.371617]\n",
      "[Epoch 55/200] [Batch 180/235] [D loss: -0.046308] [G loss: -0.351819]\n",
      "[Epoch 55/200] [Batch 185/235] [D loss: -0.026686] [G loss: -0.288198]\n",
      "[Epoch 55/200] [Batch 190/235] [D loss: -0.053544] [G loss: -0.228831]\n",
      "[Epoch 55/200] [Batch 195/235] [D loss: -0.048406] [G loss: -0.200237]\n",
      "[Epoch 55/200] [Batch 200/235] [D loss: -0.056056] [G loss: -0.291304]\n",
      "[Epoch 55/200] [Batch 205/235] [D loss: -0.048114] [G loss: 0.151152]\n",
      "[Epoch 55/200] [Batch 210/235] [D loss: -0.079401] [G loss: 0.426285]\n",
      "[Epoch 55/200] [Batch 215/235] [D loss: -0.082396] [G loss: 0.713951]\n",
      "[Epoch 55/200] [Batch 220/235] [D loss: -0.034857] [G loss: 0.047182]\n",
      "[Epoch 55/200] [Batch 225/235] [D loss: -0.097093] [G loss: -0.759164]\n",
      "[Epoch 55/200] [Batch 230/235] [D loss: -0.057871] [G loss: -0.284006]\n",
      "[Epoch 56/200] [Batch 0/235] [D loss: -0.048422] [G loss: -0.094009]\n",
      "[Epoch 56/200] [Batch 5/235] [D loss: -0.082112] [G loss: 0.052150]\n",
      "[Epoch 56/200] [Batch 10/235] [D loss: -0.065457] [G loss: -0.203872]\n",
      "[Epoch 56/200] [Batch 15/235] [D loss: -0.076009] [G loss: 0.142376]\n",
      "[Epoch 56/200] [Batch 20/235] [D loss: -0.054208] [G loss: -0.287394]\n",
      "[Epoch 56/200] [Batch 25/235] [D loss: -0.116351] [G loss: -0.474922]\n",
      "[Epoch 56/200] [Batch 30/235] [D loss: -0.074156] [G loss: 0.071877]\n",
      "[Epoch 56/200] [Batch 35/235] [D loss: -0.059119] [G loss: 0.513498]\n",
      "[Epoch 56/200] [Batch 40/235] [D loss: -0.091971] [G loss: 0.746268]\n",
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      "[Epoch 57/200] [Batch 0/235] [D loss: -0.038759] [G loss: -0.264130]\n",
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      "[Epoch 57/200] [Batch 20/235] [D loss: -0.074443] [G loss: 0.343727]\n",
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      "[Epoch 57/200] [Batch 40/235] [D loss: -0.036046] [G loss: -0.801528]\n",
      "[Epoch 57/200] [Batch 45/235] [D loss: -0.057980] [G loss: -0.818478]\n",
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      "[Epoch 57/200] [Batch 70/235] [D loss: -0.048074] [G loss: 0.256539]\n",
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      "[Epoch 57/200] [Batch 205/235] [D loss: -0.042187] [G loss: -0.442258]\n",
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      "[Epoch 58/200] [Batch 0/235] [D loss: -0.032200] [G loss: 0.366271]\n",
      "[Epoch 58/200] [Batch 5/235] [D loss: -0.070146] [G loss: 0.002077]\n",
      "[Epoch 58/200] [Batch 10/235] [D loss: -0.096912] [G loss: 0.515239]\n",
      "[Epoch 58/200] [Batch 15/235] [D loss: -0.011197] [G loss: -0.294217]\n",
      "[Epoch 58/200] [Batch 20/235] [D loss: -0.073646] [G loss: -0.412783]\n",
      "[Epoch 58/200] [Batch 25/235] [D loss: -0.080604] [G loss: -0.226826]\n",
      "[Epoch 58/200] [Batch 30/235] [D loss: -0.028493] [G loss: 0.758016]\n",
      "[Epoch 58/200] [Batch 35/235] [D loss: -0.030028] [G loss: 0.803914]\n",
      "[Epoch 58/200] [Batch 40/235] [D loss: -0.051669] [G loss: 0.624553]\n",
      "[Epoch 58/200] [Batch 45/235] [D loss: -0.053463] [G loss: 0.287624]\n",
      "[Epoch 58/200] [Batch 50/235] [D loss: -0.045637] [G loss: -0.316633]\n",
      "[Epoch 58/200] [Batch 55/235] [D loss: -0.040005] [G loss: -0.696129]\n",
      "[Epoch 58/200] [Batch 60/235] [D loss: -0.045346] [G loss: -0.956412]\n",
      "[Epoch 58/200] [Batch 65/235] [D loss: -0.051422] [G loss: -0.224045]\n",
      "[Epoch 58/200] [Batch 70/235] [D loss: -0.066255] [G loss: -0.213206]\n",
      "[Epoch 58/200] [Batch 75/235] [D loss: -0.034455] [G loss: 0.365377]\n",
      "[Epoch 58/200] [Batch 80/235] [D loss: -0.032895] [G loss: 0.320680]\n",
      "[Epoch 58/200] [Batch 85/235] [D loss: -0.037853] [G loss: 0.145878]\n",
      "[Epoch 58/200] [Batch 90/235] [D loss: -0.052469] [G loss: -0.171898]\n",
      "[Epoch 58/200] [Batch 95/235] [D loss: -0.027055] [G loss: -0.819658]\n",
      "[Epoch 58/200] [Batch 100/235] [D loss: -0.037826] [G loss: -0.390137]\n",
      "[Epoch 58/200] [Batch 105/235] [D loss: -0.053338] [G loss: -0.100735]\n",
      "[Epoch 58/200] [Batch 110/235] [D loss: -0.036868] [G loss: 0.896515]\n",
      "[Epoch 58/200] [Batch 115/235] [D loss: -0.051593] [G loss: 1.155773]\n",
      "[Epoch 58/200] [Batch 120/235] [D loss: -0.062101] [G loss: 0.067428]\n",
      "[Epoch 58/200] [Batch 125/235] [D loss: -0.064306] [G loss: -0.339485]\n",
      "[Epoch 58/200] [Batch 130/235] [D loss: -0.015007] [G loss: -0.138990]\n",
      "[Epoch 58/200] [Batch 135/235] [D loss: -0.039569] [G loss: -0.247289]\n",
      "[Epoch 58/200] [Batch 140/235] [D loss: -0.064401] [G loss: -0.299650]\n",
      "[Epoch 58/200] [Batch 145/235] [D loss: -0.041308] [G loss: -0.417160]\n",
      "[Epoch 58/200] [Batch 150/235] [D loss: -0.034326] [G loss: -0.221452]\n",
      "[Epoch 58/200] [Batch 155/235] [D loss: -0.047829] [G loss: -0.227273]\n",
      "[Epoch 58/200] [Batch 160/235] [D loss: -0.064543] [G loss: 0.165986]\n",
      "[Epoch 58/200] [Batch 165/235] [D loss: -0.043470] [G loss: 0.120728]\n",
      "[Epoch 58/200] [Batch 170/235] [D loss: -0.039562] [G loss: 0.399141]\n",
      "[Epoch 58/200] [Batch 175/235] [D loss: -0.068467] [G loss: 0.380996]\n",
      "[Epoch 58/200] [Batch 180/235] [D loss: -0.038292] [G loss: 0.142141]\n",
      "[Epoch 58/200] [Batch 185/235] [D loss: -0.033805] [G loss: -0.171876]\n",
      "[Epoch 58/200] [Batch 190/235] [D loss: -0.057050] [G loss: -0.518721]\n",
      "[Epoch 58/200] [Batch 195/235] [D loss: -0.016174] [G loss: -0.486917]\n",
      "[Epoch 58/200] [Batch 200/235] [D loss: -0.049169] [G loss: -0.591072]\n",
      "[Epoch 58/200] [Batch 205/235] [D loss: -0.041705] [G loss: 0.071872]\n",
      "[Epoch 58/200] [Batch 210/235] [D loss: -0.056509] [G loss: 0.549831]\n",
      "[Epoch 58/200] [Batch 215/235] [D loss: -0.055405] [G loss: 0.725588]\n",
      "[Epoch 58/200] [Batch 220/235] [D loss: -0.039144] [G loss: -0.020603]\n",
      "[Epoch 58/200] [Batch 225/235] [D loss: -0.067370] [G loss: -0.689658]\n",
      "[Epoch 58/200] [Batch 230/235] [D loss: -0.027754] [G loss: -0.485934]\n",
      "[Epoch 59/200] [Batch 0/235] [D loss: -0.051186] [G loss: 0.004875]\n",
      "[Epoch 59/200] [Batch 5/235] [D loss: -0.032690] [G loss: 1.183475]\n",
      "[Epoch 59/200] [Batch 10/235] [D loss: -0.041250] [G loss: 0.226431]\n",
      "[Epoch 59/200] [Batch 15/235] [D loss: -0.038690] [G loss: 0.261795]\n",
      "[Epoch 59/200] [Batch 20/235] [D loss: -0.029863] [G loss: -0.834637]\n",
      "[Epoch 59/200] [Batch 25/235] [D loss: -0.080689] [G loss: -1.013088]\n",
      "[Epoch 59/200] [Batch 30/235] [D loss: -0.043662] [G loss: -0.207462]\n",
      "[Epoch 59/200] [Batch 35/235] [D loss: -0.056609] [G loss: -0.009686]\n",
      "[Epoch 59/200] [Batch 40/235] [D loss: -0.068863] [G loss: 1.437929]\n",
      "[Epoch 59/200] [Batch 45/235] [D loss: -0.095015] [G loss: 0.703371]\n",
      "[Epoch 59/200] [Batch 50/235] [D loss: -0.043563] [G loss: -0.270994]\n",
      "[Epoch 59/200] [Batch 55/235] [D loss: -0.092126] [G loss: -0.222198]\n",
      "[Epoch 59/200] [Batch 60/235] [D loss: -0.026194] [G loss: -0.290502]\n",
      "[Epoch 59/200] [Batch 65/235] [D loss: -0.150128] [G loss: -1.278715]\n",
      "[Epoch 59/200] [Batch 70/235] [D loss: -0.054448] [G loss: -0.897558]\n",
      "[Epoch 59/200] [Batch 75/235] [D loss: -0.042212] [G loss: -0.667273]\n",
      "[Epoch 59/200] [Batch 80/235] [D loss: -0.126165] [G loss: 0.163959]\n",
      "[Epoch 59/200] [Batch 85/235] [D loss: -0.016501] [G loss: 1.568758]\n",
      "[Epoch 59/200] [Batch 90/235] [D loss: -0.119169] [G loss: 0.885104]\n",
      "[Epoch 59/200] [Batch 95/235] [D loss: -0.051843] [G loss: -0.265917]\n",
      "[Epoch 59/200] [Batch 100/235] [D loss: -0.043908] [G loss: -2.181587]\n",
      "[Epoch 59/200] [Batch 105/235] [D loss: -0.062565] [G loss: -2.232329]\n",
      "[Epoch 59/200] [Batch 110/235] [D loss: -0.021169] [G loss: -0.497021]\n",
      "[Epoch 59/200] [Batch 115/235] [D loss: -0.057953] [G loss: 1.240531]\n",
      "[Epoch 59/200] [Batch 120/235] [D loss: -0.017263] [G loss: 1.679011]\n",
      "[Epoch 59/200] [Batch 125/235] [D loss: -0.023645] [G loss: 0.435129]\n",
      "[Epoch 59/200] [Batch 130/235] [D loss: -0.047035] [G loss: -1.015721]\n",
      "[Epoch 59/200] [Batch 135/235] [D loss: -0.034825] [G loss: -1.237732]\n",
      "[Epoch 59/200] [Batch 140/235] [D loss: -0.017527] [G loss: -0.078009]\n",
      "[Epoch 59/200] [Batch 145/235] [D loss: -0.039619] [G loss: 0.921559]\n",
      "[Epoch 59/200] [Batch 150/235] [D loss: -0.039805] [G loss: 0.719364]\n",
      "[Epoch 59/200] [Batch 155/235] [D loss: -0.020309] [G loss: 0.034814]\n",
      "[Epoch 59/200] [Batch 160/235] [D loss: -0.053258] [G loss: -0.474793]\n",
      "[Epoch 59/200] [Batch 165/235] [D loss: -0.020457] [G loss: -0.448538]\n",
      "[Epoch 59/200] [Batch 170/235] [D loss: -0.033906] [G loss: -0.091925]\n",
      "[Epoch 59/200] [Batch 175/235] [D loss: -0.034872] [G loss: -0.340644]\n",
      "[Epoch 59/200] [Batch 180/235] [D loss: -0.026207] [G loss: 0.388075]\n",
      "[Epoch 59/200] [Batch 185/235] [D loss: -0.042351] [G loss: 0.326899]\n",
      "[Epoch 59/200] [Batch 190/235] [D loss: -0.030964] [G loss: 0.715830]\n",
      "[Epoch 59/200] [Batch 195/235] [D loss: -0.037202] [G loss: 0.410181]\n",
      "[Epoch 59/200] [Batch 200/235] [D loss: -0.015544] [G loss: -0.998849]\n",
      "[Epoch 59/200] [Batch 205/235] [D loss: -0.078096] [G loss: -1.522128]\n",
      "[Epoch 59/200] [Batch 210/235] [D loss: -0.020284] [G loss: -0.379415]\n",
      "[Epoch 59/200] [Batch 215/235] [D loss: -0.049668] [G loss: 0.171404]\n",
      "[Epoch 59/200] [Batch 220/235] [D loss: -0.074848] [G loss: 0.871421]\n",
      "[Epoch 59/200] [Batch 225/235] [D loss: -0.023855] [G loss: 0.127941]\n",
      "[Epoch 59/200] [Batch 230/235] [D loss: -0.030805] [G loss: -0.288464]\n",
      "[Epoch 60/200] [Batch 0/235] [D loss: -0.047633] [G loss: -0.154101]\n",
      "[Epoch 60/200] [Batch 5/235] [D loss: -0.028359] [G loss: 0.207192]\n",
      "[Epoch 60/200] [Batch 10/235] [D loss: -0.047199] [G loss: 0.496297]\n",
      "[Epoch 60/200] [Batch 15/235] [D loss: -0.058123] [G loss: 0.689645]\n",
      "[Epoch 60/200] [Batch 20/235] [D loss: -0.032879] [G loss: -0.445952]\n",
      "[Epoch 60/200] [Batch 25/235] [D loss: -0.060282] [G loss: -1.324807]\n",
      "[Epoch 60/200] [Batch 30/235] [D loss: -0.022241] [G loss: -0.977516]\n",
      "[Epoch 60/200] [Batch 35/235] [D loss: -0.034061] [G loss: -0.107592]\n",
      "[Epoch 60/200] [Batch 40/235] [D loss: -0.073476] [G loss: 1.222799]\n",
      "[Epoch 60/200] [Batch 45/235] [D loss: -0.037441] [G loss: 1.595141]\n",
      "[Epoch 60/200] [Batch 50/235] [D loss: -0.023334] [G loss: -0.006833]\n",
      "[Epoch 60/200] [Batch 55/235] [D loss: -0.089070] [G loss: -0.878343]\n",
      "[Epoch 60/200] [Batch 60/235] [D loss: -0.026026] [G loss: -0.383340]\n",
      "[Epoch 60/200] [Batch 65/235] [D loss: -0.039927] [G loss: 0.177282]\n",
      "[Epoch 60/200] [Batch 70/235] [D loss: -0.040961] [G loss: 0.696427]\n",
      "[Epoch 60/200] [Batch 75/235] [D loss: -0.035003] [G loss: 0.276212]\n",
      "[Epoch 60/200] [Batch 80/235] [D loss: -0.058501] [G loss: -1.086685]\n",
      "[Epoch 60/200] [Batch 85/235] [D loss: -0.042129] [G loss: -0.843354]\n",
      "[Epoch 60/200] [Batch 90/235] [D loss: -0.031312] [G loss: -0.225024]\n",
      "[Epoch 60/200] [Batch 95/235] [D loss: -0.045678] [G loss: 0.554429]\n",
      "[Epoch 60/200] [Batch 100/235] [D loss: -0.023625] [G loss: 1.193633]\n",
      "[Epoch 60/200] [Batch 105/235] [D loss: -0.046396] [G loss: 1.100530]\n",
      "[Epoch 60/200] [Batch 110/235] [D loss: -0.066178] [G loss: -1.009349]\n",
      "[Epoch 60/200] [Batch 115/235] [D loss: -0.064090] [G loss: -1.712306]\n",
      "[Epoch 60/200] [Batch 120/235] [D loss: -0.032775] [G loss: 0.372864]\n",
      "[Epoch 60/200] [Batch 125/235] [D loss: -0.086459] [G loss: 2.060190]\n",
      "[Epoch 60/200] [Batch 130/235] [D loss: -0.026234] [G loss: 0.497546]\n",
      "[Epoch 60/200] [Batch 135/235] [D loss: -0.031992] [G loss: -1.308171]\n",
      "[Epoch 60/200] [Batch 140/235] [D loss: -0.073630] [G loss: -1.763056]\n",
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      "[Epoch 63/200] [Batch 0/235] [D loss: -0.031561] [G loss: 0.677092]\n",
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      "[Epoch 64/200] [Batch 0/235] [D loss: -0.003392] [G loss: 0.813866]\n",
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      "[Epoch 65/200] [Batch 0/235] [D loss: -0.033311] [G loss: 1.492545]\n",
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      "[Epoch 73/200] [Batch 0/235] [D loss: 0.041110] [G loss: -0.786344]\n",
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      "[Epoch 74/200] [Batch 0/235] [D loss: -0.010690] [G loss: -1.649511]\n",
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      "[Epoch 74/200] [Batch 10/235] [D loss: -0.036113] [G loss: 3.262814]\n",
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      "[Epoch 78/200] [Batch 0/235] [D loss: -0.037503] [G loss: 1.222399]\n",
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      "[Epoch 78/200] [Batch 110/235] [D loss: -0.028758] [G loss: -1.456515]\n",
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      "[Epoch 81/200] [Batch 0/235] [D loss: -0.004839] [G loss: 0.268303]\n",
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      "[Epoch 82/200] [Batch 0/235] [D loss: -0.008681] [G loss: 0.556841]\n",
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      "[Epoch 82/200] [Batch 185/235] [D loss: -0.003422] [G loss: -0.345637]\n",
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      "[Epoch 82/200] [Batch 225/235] [D loss: -0.009718] [G loss: 0.292312]\n",
      "[Epoch 82/200] [Batch 230/235] [D loss: -0.012327] [G loss: 0.187904]\n",
      "[Epoch 83/200] [Batch 0/235] [D loss: -0.028538] [G loss: 0.435755]\n",
      "[Epoch 83/200] [Batch 5/235] [D loss: -0.019509] [G loss: -0.765583]\n",
      "[Epoch 83/200] [Batch 10/235] [D loss: -0.010890] [G loss: -1.041975]\n",
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      "[Epoch 86/200] [Batch 0/235] [D loss: -0.057218] [G loss: 1.114746]\n",
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      "[Epoch 87/200] [Batch 0/235] [D loss: -0.004634] [G loss: -0.125913]\n",
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      "[Epoch 90/200] [Batch 0/235] [D loss: -0.007151] [G loss: -0.449052]\n",
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      "[Epoch 91/200] [Batch 0/235] [D loss: -0.005072] [G loss: -0.332972]\n",
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      "[Epoch 92/200] [Batch 0/235] [D loss: 0.000991] [G loss: 0.315390]\n",
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      "[Epoch 96/200] [Batch 0/235] [D loss: -0.001629] [G loss: 0.076033]\n",
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      "[Epoch 100/200] [Batch 100/235] [D loss: -0.003716] [G loss: -0.028312]\n",
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      "[Epoch 100/200] [Batch 170/235] [D loss: -0.057787] [G loss: -2.978401]\n",
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      "[Epoch 100/200] [Batch 200/235] [D loss: -0.007476] [G loss: 0.131578]\n",
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      "[Epoch 101/200] [Batch 0/235] [D loss: -0.004378] [G loss: 0.412513]\n",
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      "[Epoch 104/200] [Batch 0/235] [D loss: -0.024961] [G loss: 0.173170]\n",
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      "[Epoch 104/200] [Batch 65/235] [D loss: -0.009083] [G loss: -0.443726]\n",
      "[Epoch 104/200] [Batch 70/235] [D loss: -0.072187] [G loss: -1.162909]\n",
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      "[Epoch 104/200] [Batch 85/235] [D loss: -0.038283] [G loss: 1.343293]\n",
      "[Epoch 104/200] [Batch 90/235] [D loss: -0.020521] [G loss: 1.025892]\n",
      "[Epoch 104/200] [Batch 95/235] [D loss: -0.002680] [G loss: 0.045977]\n",
      "[Epoch 104/200] [Batch 100/235] [D loss: -0.020820] [G loss: -0.579713]\n",
      "[Epoch 104/200] [Batch 105/235] [D loss: 0.009725] [G loss: -0.643813]\n",
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      "[Epoch 104/200] [Batch 130/235] [D loss: -0.025091] [G loss: -0.778063]\n",
      "[Epoch 104/200] [Batch 135/235] [D loss: -0.008739] [G loss: 0.079084]\n",
      "[Epoch 104/200] [Batch 140/235] [D loss: -0.020822] [G loss: 0.966562]\n",
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      "[Epoch 104/200] [Batch 150/235] [D loss: -0.007401] [G loss: 0.039059]\n",
      "[Epoch 104/200] [Batch 155/235] [D loss: -0.043588] [G loss: -0.868054]\n",
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      "[Epoch 104/200] [Batch 185/235] [D loss: -0.017055] [G loss: -0.565836]\n",
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      "[Epoch 105/200] [Batch 0/235] [D loss: -0.004900] [G loss: -0.736370]\n",
      "[Epoch 105/200] [Batch 5/235] [D loss: -0.011623] [G loss: -0.194462]\n",
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      "[Epoch 105/200] [Batch 30/235] [D loss: -0.020759] [G loss: -0.229567]\n",
      "[Epoch 105/200] [Batch 35/235] [D loss: 0.001651] [G loss: -0.250967]\n",
      "[Epoch 105/200] [Batch 40/235] [D loss: -0.000226] [G loss: -0.369738]\n",
      "[Epoch 105/200] [Batch 45/235] [D loss: -0.014947] [G loss: -0.753784]\n",
      "[Epoch 105/200] [Batch 50/235] [D loss: -0.006119] [G loss: 0.415092]\n",
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      "[Epoch 105/200] [Batch 60/235] [D loss: -0.020825] [G loss: 1.527815]\n",
      "[Epoch 105/200] [Batch 65/235] [D loss: -0.013409] [G loss: -0.585326]\n",
      "[Epoch 105/200] [Batch 70/235] [D loss: -0.032088] [G loss: -1.527282]\n",
      "[Epoch 105/200] [Batch 75/235] [D loss: -0.005716] [G loss: -0.646622]\n",
      "[Epoch 105/200] [Batch 80/235] [D loss: -0.029917] [G loss: 1.287220]\n",
      "[Epoch 105/200] [Batch 85/235] [D loss: 0.001302] [G loss: 0.928704]\n",
      "[Epoch 105/200] [Batch 90/235] [D loss: -0.019632] [G loss: -0.767214]\n",
      "[Epoch 105/200] [Batch 95/235] [D loss: -0.014959] [G loss: -1.147225]\n",
      "[Epoch 105/200] [Batch 100/235] [D loss: 0.003587] [G loss: -0.043025]\n",
      "[Epoch 105/200] [Batch 105/235] [D loss: -0.034622] [G loss: 1.216784]\n",
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      "[Epoch 105/200] [Batch 115/235] [D loss: -0.015147] [G loss: -0.388609]\n",
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      "[Epoch 108/200] [Batch 0/235] [D loss: 0.002696] [G loss: 0.056818]\n",
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      "[Epoch 109/200] [Batch 0/235] [D loss: -0.012991] [G loss: -1.295196]\n",
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      "[Epoch 109/200] [Batch 55/235] [D loss: -0.041534] [G loss: -1.338007]\n",
      "[Epoch 109/200] [Batch 60/235] [D loss: -0.023102] [G loss: -1.370683]\n",
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      "[Epoch 109/200] [Batch 85/235] [D loss: -0.098233] [G loss: -1.443122]\n",
      "[Epoch 109/200] [Batch 90/235] [D loss: 0.000523] [G loss: -0.221077]\n",
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      "[Epoch 109/200] [Batch 100/235] [D loss: -0.036738] [G loss: 1.964233]\n",
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      "[Epoch 109/200] [Batch 140/235] [D loss: -0.001647] [G loss: -0.632030]\n",
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      "[Epoch 109/200] [Batch 150/235] [D loss: -0.013201] [G loss: -0.465533]\n",
      "[Epoch 109/200] [Batch 155/235] [D loss: -0.025839] [G loss: -0.339713]\n",
      "[Epoch 109/200] [Batch 160/235] [D loss: 0.000455] [G loss: 0.653541]\n",
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      "[Epoch 109/200] [Batch 200/235] [D loss: -0.021730] [G loss: -0.269713]\n",
      "[Epoch 109/200] [Batch 205/235] [D loss: -0.007463] [G loss: -0.296280]\n",
      "[Epoch 109/200] [Batch 210/235] [D loss: -0.007636] [G loss: 0.165582]\n",
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      "[Epoch 109/200] [Batch 225/235] [D loss: -0.021203] [G loss: 0.566953]\n",
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      "[Epoch 110/200] [Batch 0/235] [D loss: -0.009607] [G loss: -0.493055]\n",
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      "[Epoch 114/200] [Batch 95/235] [D loss: -0.004421] [G loss: -0.308024]\n",
      "[Epoch 114/200] [Batch 100/235] [D loss: -0.003196] [G loss: -0.447277]\n",
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      "[Epoch 117/200] [Batch 0/235] [D loss: -0.005980] [G loss: -0.597113]\n",
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      "[Epoch 118/200] [Batch 0/235] [D loss: 0.004865] [G loss: -0.197486]\n",
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      "[Epoch 118/200] [Batch 40/235] [D loss: -0.003612] [G loss: 0.364115]\n",
      "[Epoch 118/200] [Batch 45/235] [D loss: -0.019588] [G loss: -0.267249]\n",
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      "[Epoch 118/200] [Batch 55/235] [D loss: -0.003886] [G loss: 0.265071]\n",
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      "[Epoch 118/200] [Batch 75/235] [D loss: 0.006356] [G loss: -0.500204]\n",
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      "[Epoch 118/200] [Batch 90/235] [D loss: -0.004620] [G loss: 1.675987]\n",
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      "[Epoch 118/200] [Batch 100/235] [D loss: -0.043196] [G loss: -1.454712]\n",
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      "[Epoch 118/200] [Batch 115/235] [D loss: -0.047145] [G loss: 2.008049]\n",
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      "[Epoch 118/200] [Batch 140/235] [D loss: -0.009561] [G loss: 0.378221]\n",
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      "[Epoch 118/200] [Batch 155/235] [D loss: -0.001725] [G loss: 0.031378]\n",
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      "[Epoch 118/200] [Batch 210/235] [D loss: -0.000959] [G loss: 0.899420]\n",
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      "[Epoch 118/200] [Batch 230/235] [D loss: -0.000677] [G loss: -0.626683]\n",
      "[Epoch 119/200] [Batch 0/235] [D loss: -0.004587] [G loss: -0.031960]\n",
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      "[Epoch 121/200] [Batch 0/235] [D loss: -0.016118] [G loss: 0.524411]\n",
      "[Epoch 121/200] [Batch 5/235] [D loss: 0.001479] [G loss: -0.192575]\n",
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      "[Epoch 121/200] [Batch 120/235] [D loss: -0.024671] [G loss: -0.439159]\n",
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      "[Epoch 121/200] [Batch 170/235] [D loss: -0.018067] [G loss: 0.596596]\n",
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      "[Epoch 121/200] [Batch 200/235] [D loss: -0.002787] [G loss: -0.285350]\n",
      "[Epoch 121/200] [Batch 205/235] [D loss: -0.017610] [G loss: -0.338827]\n",
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      "[Epoch 121/200] [Batch 215/235] [D loss: -0.001783] [G loss: -0.437643]\n",
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      "[Epoch 122/200] [Batch 0/235] [D loss: -0.006060] [G loss: 1.266544]\n",
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      "[Epoch 122/200] [Batch 10/235] [D loss: -0.002340] [G loss: -0.055349]\n",
      "[Epoch 122/200] [Batch 15/235] [D loss: -0.010040] [G loss: -0.024746]\n",
      "[Epoch 122/200] [Batch 20/235] [D loss: -0.007151] [G loss: -0.365884]\n",
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      "[Epoch 122/200] [Batch 35/235] [D loss: -0.001269] [G loss: -0.346355]\n",
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      "[Epoch 122/200] [Batch 45/235] [D loss: 0.000873] [G loss: 0.377693]\n",
      "[Epoch 122/200] [Batch 50/235] [D loss: -0.007959] [G loss: 0.228007]\n",
      "[Epoch 122/200] [Batch 55/235] [D loss: -0.017393] [G loss: 0.068779]\n",
      "[Epoch 122/200] [Batch 60/235] [D loss: -0.012770] [G loss: -0.271067]\n",
      "[Epoch 122/200] [Batch 65/235] [D loss: -0.041627] [G loss: -0.431283]\n",
      "[Epoch 122/200] [Batch 70/235] [D loss: 0.002825] [G loss: 0.056621]\n",
      "[Epoch 122/200] [Batch 75/235] [D loss: -0.006945] [G loss: -0.209195]\n",
      "[Epoch 122/200] [Batch 80/235] [D loss: -0.019610] [G loss: 0.040415]\n",
      "[Epoch 122/200] [Batch 85/235] [D loss: -0.011662] [G loss: 0.470033]\n",
      "[Epoch 122/200] [Batch 90/235] [D loss: -0.006376] [G loss: 0.735438]\n",
      "[Epoch 122/200] [Batch 95/235] [D loss: -0.004848] [G loss: 0.657928]\n",
      "[Epoch 122/200] [Batch 100/235] [D loss: -0.006798] [G loss: 0.343703]\n",
      "[Epoch 122/200] [Batch 105/235] [D loss: -0.009016] [G loss: -0.061462]\n",
      "[Epoch 122/200] [Batch 110/235] [D loss: -0.016827] [G loss: -0.575719]\n",
      "[Epoch 122/200] [Batch 115/235] [D loss: -0.012598] [G loss: -0.492858]\n",
      "[Epoch 122/200] [Batch 120/235] [D loss: -0.002823] [G loss: -0.140171]\n",
      "[Epoch 122/200] [Batch 125/235] [D loss: -0.009820] [G loss: 0.233981]\n",
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      "[Epoch 122/200] [Batch 135/235] [D loss: -0.015874] [G loss: -0.092928]\n",
      "[Epoch 122/200] [Batch 140/235] [D loss: -0.017426] [G loss: -0.044386]\n",
      "[Epoch 122/200] [Batch 145/235] [D loss: -0.021116] [G loss: -0.337621]\n",
      "[Epoch 122/200] [Batch 150/235] [D loss: -0.000629] [G loss: -0.217817]\n",
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      "[Epoch 122/200] [Batch 160/235] [D loss: -0.023201] [G loss: 0.543494]\n",
      "[Epoch 122/200] [Batch 165/235] [D loss: -0.007382] [G loss: -0.051290]\n",
      "[Epoch 122/200] [Batch 170/235] [D loss: -0.029050] [G loss: -0.287964]\n",
      "[Epoch 122/200] [Batch 175/235] [D loss: -0.009148] [G loss: -0.162780]\n",
      "[Epoch 122/200] [Batch 180/235] [D loss: -0.005839] [G loss: 0.218957]\n",
      "[Epoch 122/200] [Batch 185/235] [D loss: -0.010793] [G loss: 0.542574]\n",
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      "[Epoch 122/200] [Batch 200/235] [D loss: -0.006299] [G loss: -0.298220]\n",
      "[Epoch 122/200] [Batch 205/235] [D loss: -0.025265] [G loss: -0.877264]\n",
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      "[Epoch 122/200] [Batch 215/235] [D loss: -0.005304] [G loss: -0.273857]\n",
      "[Epoch 122/200] [Batch 220/235] [D loss: -0.005727] [G loss: -0.041670]\n",
      "[Epoch 122/200] [Batch 225/235] [D loss: -0.005904] [G loss: 0.085734]\n",
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      "[Epoch 123/200] [Batch 0/235] [D loss: 0.001148] [G loss: 0.027937]\n",
      "[Epoch 123/200] [Batch 5/235] [D loss: -0.009496] [G loss: 0.582904]\n",
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      "[Epoch 123/200] [Batch 20/235] [D loss: -0.003009] [G loss: 0.061221]\n",
      "[Epoch 123/200] [Batch 25/235] [D loss: -0.028232] [G loss: -0.558616]\n",
      "[Epoch 123/200] [Batch 30/235] [D loss: -0.014963] [G loss: -0.635834]\n",
      "[Epoch 123/200] [Batch 35/235] [D loss: -0.001857] [G loss: -0.602894]\n",
      "[Epoch 123/200] [Batch 40/235] [D loss: -0.010275] [G loss: -0.228131]\n",
      "[Epoch 123/200] [Batch 45/235] [D loss: -0.008439] [G loss: 0.450840]\n",
      "[Epoch 123/200] [Batch 50/235] [D loss: -0.014928] [G loss: 0.834847]\n",
      "[Epoch 123/200] [Batch 55/235] [D loss: -0.009863] [G loss: 0.862942]\n",
      "[Epoch 123/200] [Batch 60/235] [D loss: -0.009518] [G loss: 0.481452]\n",
      "[Epoch 123/200] [Batch 65/235] [D loss: -0.022559] [G loss: -0.165520]\n",
      "[Epoch 123/200] [Batch 70/235] [D loss: -0.009312] [G loss: -0.000159]\n",
      "[Epoch 123/200] [Batch 75/235] [D loss: -0.008782] [G loss: 0.105442]\n",
      "[Epoch 123/200] [Batch 80/235] [D loss: -0.004893] [G loss: 0.445631]\n",
      "[Epoch 123/200] [Batch 85/235] [D loss: -0.021187] [G loss: 0.330802]\n",
      "[Epoch 123/200] [Batch 90/235] [D loss: -0.003882] [G loss: -0.152473]\n",
      "[Epoch 123/200] [Batch 95/235] [D loss: -0.008962] [G loss: -0.767652]\n",
      "[Epoch 123/200] [Batch 100/235] [D loss: -0.015513] [G loss: -0.730422]\n",
      "[Epoch 123/200] [Batch 105/235] [D loss: 0.003906] [G loss: -0.124241]\n",
      "[Epoch 123/200] [Batch 110/235] [D loss: -0.008861] [G loss: 0.432035]\n",
      "[Epoch 123/200] [Batch 115/235] [D loss: 0.003267] [G loss: 0.502780]\n",
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      "[Epoch 126/200] [Batch 0/235] [D loss: -0.013790] [G loss: -1.329150]\n",
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      "[Epoch 130/200] [Batch 0/235] [D loss: -0.027894] [G loss: 0.594421]\n",
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      "[Epoch 131/200] [Batch 0/235] [D loss: -0.038669] [G loss: 1.749731]\n",
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      "[Epoch 131/200] [Batch 40/235] [D loss: -0.008833] [G loss: -0.454909]\n",
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      "[Epoch 131/200] [Batch 100/235] [D loss: -0.041242] [G loss: -0.680943]\n",
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      "[Epoch 132/200] [Batch 0/235] [D loss: -0.009774] [G loss: 0.179460]\n",
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      "[Epoch 132/200] [Batch 30/235] [D loss: -0.027030] [G loss: -1.240589]\n",
      "[Epoch 132/200] [Batch 35/235] [D loss: -0.005512] [G loss: -0.485633]\n",
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      "[Epoch 132/200] [Batch 45/235] [D loss: -0.019804] [G loss: 1.361575]\n",
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      "[Epoch 132/200] [Batch 55/235] [D loss: -0.024296] [G loss: -0.769522]\n",
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      "[Epoch 132/200] [Batch 65/235] [D loss: -0.013841] [G loss: -0.096754]\n",
      "[Epoch 132/200] [Batch 70/235] [D loss: -0.007526] [G loss: 0.983025]\n",
      "[Epoch 132/200] [Batch 75/235] [D loss: 0.005740] [G loss: 0.808093]\n",
      "[Epoch 132/200] [Batch 80/235] [D loss: -0.014059] [G loss: 0.307465]\n",
      "[Epoch 132/200] [Batch 85/235] [D loss: -0.023836] [G loss: -0.400830]\n",
      "[Epoch 132/200] [Batch 90/235] [D loss: -0.015930] [G loss: 0.549874]\n",
      "[Epoch 132/200] [Batch 95/235] [D loss: -0.004621] [G loss: 0.146792]\n",
      "[Epoch 132/200] [Batch 100/235] [D loss: -0.018099] [G loss: -0.011645]\n",
      "[Epoch 132/200] [Batch 105/235] [D loss: -0.007117] [G loss: 0.303489]\n",
      "[Epoch 132/200] [Batch 110/235] [D loss: -0.016277] [G loss: -0.958833]\n",
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      "[Epoch 135/200] [Batch 0/235] [D loss: -0.031993] [G loss: -0.772448]\n",
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      "[Epoch 135/200] [Batch 100/235] [D loss: -0.012825] [G loss: 0.025835]\n",
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      "[Epoch 135/200] [Batch 135/235] [D loss: -0.009779] [G loss: -0.691983]\n",
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      "[Epoch 135/200] [Batch 150/235] [D loss: -0.008112] [G loss: 0.689021]\n",
      "[Epoch 135/200] [Batch 155/235] [D loss: -0.030786] [G loss: -0.490245]\n",
      "[Epoch 135/200] [Batch 160/235] [D loss: -0.004865] [G loss: -1.248684]\n",
      "[Epoch 135/200] [Batch 165/235] [D loss: -0.002908] [G loss: -0.450982]\n",
      "[Epoch 135/200] [Batch 170/235] [D loss: -0.017387] [G loss: 0.621721]\n",
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      "[Epoch 135/200] [Batch 180/235] [D loss: -0.015479] [G loss: -0.702718]\n",
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      "[Epoch 135/200] [Batch 190/235] [D loss: -0.003863] [G loss: -0.443975]\n",
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      "[Epoch 135/200] [Batch 200/235] [D loss: -0.034935] [G loss: 1.073391]\n",
      "[Epoch 135/200] [Batch 205/235] [D loss: -0.013654] [G loss: -0.798817]\n",
      "[Epoch 135/200] [Batch 210/235] [D loss: -0.005876] [G loss: -0.665352]\n",
      "[Epoch 135/200] [Batch 215/235] [D loss: -0.012413] [G loss: -0.180911]\n",
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      "[Epoch 136/200] [Batch 0/235] [D loss: 0.006710] [G loss: -0.423326]\n",
      "[Epoch 136/200] [Batch 5/235] [D loss: 0.011665] [G loss: -0.153625]\n",
      "[Epoch 136/200] [Batch 10/235] [D loss: -0.008299] [G loss: 0.126837]\n",
      "[Epoch 136/200] [Batch 15/235] [D loss: -0.027511] [G loss: 0.496033]\n",
      "[Epoch 136/200] [Batch 20/235] [D loss: 0.008264] [G loss: -0.203060]\n",
      "[Epoch 136/200] [Batch 25/235] [D loss: -0.012811] [G loss: 0.316029]\n",
      "[Epoch 136/200] [Batch 30/235] [D loss: 0.003489] [G loss: -0.341163]\n",
      "[Epoch 136/200] [Batch 35/235] [D loss: -0.017582] [G loss: 0.491358]\n",
      "[Epoch 136/200] [Batch 40/235] [D loss: -0.009638] [G loss: 0.760311]\n",
      "[Epoch 136/200] [Batch 45/235] [D loss: -0.030368] [G loss: -1.033008]\n",
      "[Epoch 136/200] [Batch 50/235] [D loss: -0.005272] [G loss: -0.181991]\n",
      "[Epoch 136/200] [Batch 55/235] [D loss: -0.024764] [G loss: 0.987097]\n",
      "[Epoch 136/200] [Batch 60/235] [D loss: -0.010225] [G loss: -0.200934]\n",
      "[Epoch 136/200] [Batch 65/235] [D loss: -0.022709] [G loss: -1.473201]\n",
      "[Epoch 136/200] [Batch 70/235] [D loss: -0.004994] [G loss: -0.851016]\n",
      "[Epoch 136/200] [Batch 75/235] [D loss: -0.033375] [G loss: 1.589838]\n",
      "[Epoch 136/200] [Batch 80/235] [D loss: -0.013864] [G loss: 0.880730]\n",
      "[Epoch 136/200] [Batch 85/235] [D loss: -0.019801] [G loss: -0.660786]\n",
      "[Epoch 136/200] [Batch 90/235] [D loss: -0.001695] [G loss: -0.505118]\n",
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      "[Epoch 136/200] [Batch 100/235] [D loss: -0.012599] [G loss: 0.220565]\n",
      "[Epoch 136/200] [Batch 105/235] [D loss: -0.021739] [G loss: 0.026859]\n",
      "[Epoch 136/200] [Batch 110/235] [D loss: -0.004739] [G loss: 0.126444]\n",
      "[Epoch 136/200] [Batch 115/235] [D loss: -0.008890] [G loss: -0.043175]\n",
      "[Epoch 136/200] [Batch 120/235] [D loss: -0.016593] [G loss: 0.614358]\n",
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      "[Epoch 136/200] [Batch 135/235] [D loss: -0.007021] [G loss: 0.036021]\n",
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      "[Epoch 136/200] [Batch 145/235] [D loss: -0.015677] [G loss: 0.744812]\n",
      "[Epoch 136/200] [Batch 150/235] [D loss: -0.059381] [G loss: -2.164437]\n",
      "[Epoch 136/200] [Batch 155/235] [D loss: 0.010820] [G loss: -0.439410]\n",
      "[Epoch 136/200] [Batch 160/235] [D loss: -0.004885] [G loss: 0.736239]\n",
      "[Epoch 136/200] [Batch 165/235] [D loss: -0.033741] [G loss: 2.354056]\n",
      "[Epoch 136/200] [Batch 170/235] [D loss: -0.003624] [G loss: 0.929157]\n",
      "[Epoch 136/200] [Batch 175/235] [D loss: -0.031171] [G loss: 0.237598]\n",
      "[Epoch 136/200] [Batch 180/235] [D loss: -0.001948] [G loss: -0.443039]\n",
      "[Epoch 136/200] [Batch 185/235] [D loss: -0.021895] [G loss: 1.127674]\n",
      "[Epoch 136/200] [Batch 190/235] [D loss: -0.014802] [G loss: 1.282897]\n",
      "[Epoch 136/200] [Batch 195/235] [D loss: -0.004622] [G loss: -0.168695]\n",
      "[Epoch 136/200] [Batch 200/235] [D loss: -0.053873] [G loss: -1.341896]\n",
      "[Epoch 136/200] [Batch 205/235] [D loss: 0.001495] [G loss: -0.674950]\n",
      "[Epoch 136/200] [Batch 210/235] [D loss: -0.018532] [G loss: 1.045271]\n",
      "[Epoch 136/200] [Batch 215/235] [D loss: -0.014430] [G loss: 0.637476]\n",
      "[Epoch 136/200] [Batch 220/235] [D loss: -0.013733] [G loss: -0.069591]\n",
      "[Epoch 136/200] [Batch 225/235] [D loss: -0.029489] [G loss: -1.267133]\n",
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      "[Epoch 139/200] [Batch 0/235] [D loss: -0.012853] [G loss: 1.138218]\n",
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      "[Epoch 140/200] [Batch 85/235] [D loss: -0.005064] [G loss: -0.111802]\n",
      "[Epoch 140/200] [Batch 90/235] [D loss: -0.025783] [G loss: 1.182712]\n",
      "[Epoch 140/200] [Batch 95/235] [D loss: 0.010264] [G loss: 0.332495]\n",
      "[Epoch 140/200] [Batch 100/235] [D loss: -0.009710] [G loss: -0.562157]\n",
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      "[Epoch 140/200] [Batch 150/235] [D loss: -0.021835] [G loss: -0.765492]\n",
      "[Epoch 140/200] [Batch 155/235] [D loss: -0.003304] [G loss: -0.071482]\n",
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      "[Epoch 140/200] [Batch 165/235] [D loss: -0.020718] [G loss: 0.888621]\n",
      "[Epoch 140/200] [Batch 170/235] [D loss: -0.022542] [G loss: -0.928043]\n",
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      "[Epoch 140/200] [Batch 200/235] [D loss: -0.007598] [G loss: 0.066776]\n",
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      "[Epoch 141/200] [Batch 0/235] [D loss: -0.027867] [G loss: -0.565415]\n",
      "[Epoch 141/200] [Batch 5/235] [D loss: -0.013938] [G loss: -1.117595]\n",
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      "[Epoch 141/200] [Batch 35/235] [D loss: -0.031562] [G loss: 0.924615]\n",
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      "[Epoch 141/200] [Batch 55/235] [D loss: -0.012066] [G loss: -0.641407]\n",
      "[Epoch 141/200] [Batch 60/235] [D loss: -0.022455] [G loss: -1.286101]\n",
      "[Epoch 141/200] [Batch 65/235] [D loss: -0.014618] [G loss: -1.123024]\n",
      "[Epoch 141/200] [Batch 70/235] [D loss: -0.008769] [G loss: 0.142319]\n",
      "[Epoch 141/200] [Batch 75/235] [D loss: -0.011321] [G loss: 0.281312]\n",
      "[Epoch 141/200] [Batch 80/235] [D loss: -0.012527] [G loss: 0.837581]\n",
      "[Epoch 141/200] [Batch 85/235] [D loss: -0.005225] [G loss: 0.959853]\n",
      "[Epoch 141/200] [Batch 90/235] [D loss: -0.001455] [G loss: 0.087815]\n",
      "[Epoch 141/200] [Batch 95/235] [D loss: -0.030071] [G loss: -0.403121]\n",
      "[Epoch 141/200] [Batch 100/235] [D loss: -0.036818] [G loss: -0.526102]\n",
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      "[Epoch 143/200] [Batch 0/235] [D loss: -0.043985] [G loss: 0.332703]\n",
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      "[Epoch 143/200] [Batch 85/235] [D loss: -0.026801] [G loss: 1.061433]\n",
      "[Epoch 143/200] [Batch 90/235] [D loss: -0.016752] [G loss: 2.148212]\n",
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      "[Epoch 143/200] [Batch 100/235] [D loss: -0.058613] [G loss: -0.801954]\n",
      "[Epoch 143/200] [Batch 105/235] [D loss: -0.004833] [G loss: 0.251534]\n",
      "[Epoch 143/200] [Batch 110/235] [D loss: -0.061351] [G loss: 1.484478]\n",
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      "[Epoch 143/200] [Batch 120/235] [D loss: -0.008495] [G loss: 0.187492]\n",
      "[Epoch 143/200] [Batch 125/235] [D loss: -0.060442] [G loss: -1.195752]\n",
      "[Epoch 143/200] [Batch 130/235] [D loss: -0.011087] [G loss: -0.710735]\n",
      "[Epoch 143/200] [Batch 135/235] [D loss: -0.017649] [G loss: 0.638047]\n",
      "[Epoch 143/200] [Batch 140/235] [D loss: -0.109927] [G loss: 1.708736]\n",
      "[Epoch 143/200] [Batch 145/235] [D loss: -0.006307] [G loss: -0.214409]\n",
      "[Epoch 143/200] [Batch 150/235] [D loss: -0.011820] [G loss: -1.269359]\n",
      "[Epoch 143/200] [Batch 155/235] [D loss: -0.016407] [G loss: -0.825984]\n",
      "[Epoch 143/200] [Batch 160/235] [D loss: 0.011759] [G loss: -0.233040]\n",
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      "[Epoch 143/200] [Batch 185/235] [D loss: -0.000563] [G loss: -0.886504]\n",
      "[Epoch 143/200] [Batch 190/235] [D loss: -0.007807] [G loss: 0.113526]\n",
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      "[Epoch 143/200] [Batch 200/235] [D loss: -0.009282] [G loss: 0.972665]\n",
      "[Epoch 143/200] [Batch 205/235] [D loss: 0.001052] [G loss: 0.693093]\n",
      "[Epoch 143/200] [Batch 210/235] [D loss: -0.013530] [G loss: 0.061161]\n",
      "[Epoch 143/200] [Batch 215/235] [D loss: -0.031921] [G loss: -0.905875]\n",
      "[Epoch 143/200] [Batch 220/235] [D loss: -0.014175] [G loss: 0.066389]\n",
      "[Epoch 143/200] [Batch 225/235] [D loss: -0.030828] [G loss: 1.162877]\n",
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      "[Epoch 144/200] [Batch 0/235] [D loss: -0.008323] [G loss: 0.714385]\n",
      "[Epoch 144/200] [Batch 5/235] [D loss: -0.045938] [G loss: -1.060966]\n",
      "[Epoch 144/200] [Batch 10/235] [D loss: -0.076377] [G loss: -0.685512]\n",
      "[Epoch 144/200] [Batch 15/235] [D loss: -0.000988] [G loss: -0.754340]\n",
      "[Epoch 144/200] [Batch 20/235] [D loss: -0.022793] [G loss: 0.180523]\n",
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      "[Epoch 144/200] [Batch 30/235] [D loss: -0.009932] [G loss: -0.251616]\n",
      "[Epoch 144/200] [Batch 35/235] [D loss: -0.036217] [G loss: -0.725240]\n",
      "[Epoch 144/200] [Batch 40/235] [D loss: -0.023681] [G loss: -0.703288]\n",
      "[Epoch 144/200] [Batch 45/235] [D loss: 0.019858] [G loss: -0.670064]\n",
      "[Epoch 144/200] [Batch 50/235] [D loss: -0.020068] [G loss: -0.362293]\n",
      "[Epoch 144/200] [Batch 55/235] [D loss: -0.026846] [G loss: -0.182610]\n",
      "[Epoch 144/200] [Batch 60/235] [D loss: -0.011469] [G loss: -0.308929]\n",
      "[Epoch 144/200] [Batch 65/235] [D loss: -0.003066] [G loss: -0.144901]\n",
      "[Epoch 144/200] [Batch 70/235] [D loss: -0.004025] [G loss: -0.031847]\n",
      "[Epoch 144/200] [Batch 75/235] [D loss: -0.017854] [G loss: 0.026713]\n",
      "[Epoch 144/200] [Batch 80/235] [D loss: -0.033404] [G loss: -0.150315]\n",
      "[Epoch 144/200] [Batch 85/235] [D loss: 0.007827] [G loss: 0.236481]\n",
      "[Epoch 144/200] [Batch 90/235] [D loss: -0.008731] [G loss: 0.095369]\n",
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      "[Epoch 144/200] [Batch 100/235] [D loss: -0.006799] [G loss: -0.034216]\n",
      "[Epoch 144/200] [Batch 105/235] [D loss: -0.015522] [G loss: -0.085593]\n",
      "[Epoch 144/200] [Batch 110/235] [D loss: -0.012206] [G loss: -0.130911]\n",
      "[Epoch 144/200] [Batch 115/235] [D loss: -0.008914] [G loss: 0.006631]\n",
      "[Epoch 144/200] [Batch 120/235] [D loss: -0.016840] [G loss: 0.085078]\n",
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      "[Epoch 144/200] [Batch 130/235] [D loss: 0.005221] [G loss: -0.279709]\n",
      "[Epoch 144/200] [Batch 135/235] [D loss: -0.001692] [G loss: -0.347611]\n",
      "[Epoch 144/200] [Batch 140/235] [D loss: -0.021982] [G loss: -0.381634]\n",
      "[Epoch 144/200] [Batch 145/235] [D loss: -0.025367] [G loss: -0.398528]\n",
      "[Epoch 144/200] [Batch 150/235] [D loss: 0.046194] [G loss: 0.021294]\n",
      "[Epoch 144/200] [Batch 155/235] [D loss: -0.004006] [G loss: 0.061015]\n",
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      "[Epoch 144/200] [Batch 165/235] [D loss: -0.013779] [G loss: -0.021788]\n",
      "[Epoch 144/200] [Batch 170/235] [D loss: -0.023083] [G loss: 0.115842]\n",
      "[Epoch 144/200] [Batch 175/235] [D loss: -0.009189] [G loss: 0.203040]\n",
      "[Epoch 144/200] [Batch 180/235] [D loss: -0.001853] [G loss: 0.253537]\n",
      "[Epoch 144/200] [Batch 185/235] [D loss: -0.000432] [G loss: 0.226786]\n",
      "[Epoch 144/200] [Batch 190/235] [D loss: -0.015821] [G loss: 0.203321]\n",
      "[Epoch 144/200] [Batch 195/235] [D loss: -0.010043] [G loss: -0.080833]\n",
      "[Epoch 144/200] [Batch 200/235] [D loss: -0.020321] [G loss: -0.082344]\n",
      "[Epoch 144/200] [Batch 205/235] [D loss: -0.008193] [G loss: -0.238200]\n",
      "[Epoch 144/200] [Batch 210/235] [D loss: -0.003448] [G loss: -0.307822]\n",
      "[Epoch 144/200] [Batch 215/235] [D loss: -0.015410] [G loss: -0.298833]\n",
      "[Epoch 144/200] [Batch 220/235] [D loss: -0.004374] [G loss: -0.254844]\n",
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      "[Epoch 145/200] [Batch 0/235] [D loss: -0.004049] [G loss: 0.108020]\n",
      "[Epoch 145/200] [Batch 5/235] [D loss: -0.013347] [G loss: 0.053473]\n",
      "[Epoch 145/200] [Batch 10/235] [D loss: -0.002812] [G loss: -0.061437]\n",
      "[Epoch 145/200] [Batch 15/235] [D loss: -0.011152] [G loss: -0.139820]\n",
      "[Epoch 145/200] [Batch 20/235] [D loss: -0.017024] [G loss: -0.106447]\n",
      "[Epoch 145/200] [Batch 25/235] [D loss: -0.009405] [G loss: 0.209208]\n",
      "[Epoch 145/200] [Batch 30/235] [D loss: -0.005305] [G loss: 0.329921]\n",
      "[Epoch 145/200] [Batch 35/235] [D loss: -0.013306] [G loss: 0.197835]\n",
      "[Epoch 145/200] [Batch 40/235] [D loss: -0.009785] [G loss: 0.309045]\n",
      "[Epoch 145/200] [Batch 45/235] [D loss: 0.005817] [G loss: 0.230571]\n",
      "[Epoch 145/200] [Batch 50/235] [D loss: -0.003287] [G loss: 0.045228]\n",
      "[Epoch 145/200] [Batch 55/235] [D loss: -0.010251] [G loss: -0.367918]\n",
      "[Epoch 145/200] [Batch 60/235] [D loss: -0.010493] [G loss: -0.520103]\n",
      "[Epoch 145/200] [Batch 65/235] [D loss: -0.011433] [G loss: -0.446013]\n",
      "[Epoch 145/200] [Batch 70/235] [D loss: -0.017382] [G loss: -0.418256]\n",
      "[Epoch 145/200] [Batch 75/235] [D loss: -0.007142] [G loss: -0.043632]\n",
      "[Epoch 145/200] [Batch 80/235] [D loss: -0.018785] [G loss: 0.361015]\n",
      "[Epoch 145/200] [Batch 85/235] [D loss: -0.002862] [G loss: 0.245667]\n",
      "[Epoch 145/200] [Batch 90/235] [D loss: 0.006811] [G loss: 0.261375]\n",
      "[Epoch 145/200] [Batch 95/235] [D loss: -0.005285] [G loss: -0.054647]\n",
      "[Epoch 145/200] [Batch 100/235] [D loss: -0.046952] [G loss: -0.442147]\n",
      "[Epoch 145/200] [Batch 105/235] [D loss: -0.000508] [G loss: -0.556603]\n",
      "[Epoch 145/200] [Batch 110/235] [D loss: -0.004636] [G loss: -0.148140]\n",
      "[Epoch 145/200] [Batch 115/235] [D loss: -0.008705] [G loss: 0.001737]\n",
      "[Epoch 145/200] [Batch 120/235] [D loss: -0.042072] [G loss: 2.261258]\n",
      "[Epoch 145/200] [Batch 125/235] [D loss: -0.021837] [G loss: -0.779860]\n",
      "[Epoch 145/200] [Batch 130/235] [D loss: -0.067408] [G loss: -1.536261]\n",
      "[Epoch 145/200] [Batch 135/235] [D loss: -0.013001] [G loss: 0.056594]\n",
      "[Epoch 145/200] [Batch 140/235] [D loss: -0.117229] [G loss: 3.022424]\n",
      "[Epoch 145/200] [Batch 145/235] [D loss: 0.012975] [G loss: 0.547413]\n",
      "[Epoch 145/200] [Batch 150/235] [D loss: -0.038109] [G loss: -1.249165]\n",
      "[Epoch 145/200] [Batch 155/235] [D loss: -0.019815] [G loss: -1.510944]\n",
      "[Epoch 145/200] [Batch 160/235] [D loss: -0.006096] [G loss: -0.111764]\n",
      "[Epoch 145/200] [Batch 165/235] [D loss: -0.051107] [G loss: 1.681464]\n",
      "[Epoch 145/200] [Batch 170/235] [D loss: -0.007998] [G loss: 1.115533]\n",
      "[Epoch 145/200] [Batch 175/235] [D loss: -0.018557] [G loss: -0.854031]\n",
      "[Epoch 145/200] [Batch 180/235] [D loss: -0.050334] [G loss: -1.446021]\n",
      "[Epoch 145/200] [Batch 185/235] [D loss: -0.005522] [G loss: -0.705441]\n",
      "[Epoch 145/200] [Batch 190/235] [D loss: -0.067510] [G loss: 2.270374]\n",
      "[Epoch 145/200] [Batch 195/235] [D loss: 0.001495] [G loss: 2.046487]\n",
      "[Epoch 145/200] [Batch 200/235] [D loss: -0.001367] [G loss: 0.782868]\n",
      "[Epoch 145/200] [Batch 205/235] [D loss: -0.038616] [G loss: -0.998723]\n",
      "[Epoch 145/200] [Batch 210/235] [D loss: -0.019536] [G loss: -0.626988]\n",
      "[Epoch 145/200] [Batch 215/235] [D loss: -0.002807] [G loss: 0.856509]\n",
      "[Epoch 145/200] [Batch 220/235] [D loss: -0.024050] [G loss: 1.603038]\n",
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      "[Epoch 149/200] [Batch 55/235] [D loss: -0.014062] [G loss: 0.026503]\n",
      "[Epoch 149/200] [Batch 60/235] [D loss: -0.009551] [G loss: -0.244728]\n",
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      "[Epoch 149/200] [Batch 70/235] [D loss: -0.024579] [G loss: -0.126763]\n",
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      "[Epoch 149/200] [Batch 100/235] [D loss: -0.022400] [G loss: -0.235469]\n",
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      "[Epoch 150/200] [Batch 0/235] [D loss: -0.044879] [G loss: -0.952077]\n",
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      "[Epoch 150/200] [Batch 85/235] [D loss: -0.011451] [G loss: -1.503115]\n",
      "[Epoch 150/200] [Batch 90/235] [D loss: -0.011217] [G loss: 0.114098]\n",
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      "[Epoch 159/200] [Batch 0/235] [D loss: -0.017035] [G loss: 0.559116]\n",
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      "[Epoch 168/200] [Batch 0/235] [D loss: -0.014352] [G loss: -0.163046]\n",
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      "[Epoch 168/200] [Batch 75/235] [D loss: -0.048546] [G loss: 1.717427]\n",
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      "[Epoch 168/200] [Batch 170/235] [D loss: -0.021629] [G loss: 0.477860]\n",
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      "[Epoch 169/200] [Batch 0/235] [D loss: 0.002871] [G loss: 0.194225]\n",
      "[Epoch 169/200] [Batch 5/235] [D loss: -0.083275] [G loss: -1.034418]\n",
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      "[Epoch 169/200] [Batch 20/235] [D loss: -0.025359] [G loss: 0.584462]\n",
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      "[Epoch 169/200] [Batch 35/235] [D loss: 0.002940] [G loss: -0.986879]\n",
      "[Epoch 169/200] [Batch 40/235] [D loss: -0.014160] [G loss: 0.445821]\n",
      "[Epoch 169/200] [Batch 45/235] [D loss: -0.046135] [G loss: 0.579140]\n",
      "[Epoch 169/200] [Batch 50/235] [D loss: 0.019241] [G loss: 0.271701]\n",
      "[Epoch 169/200] [Batch 55/235] [D loss: -0.011551] [G loss: -0.380133]\n",
      "[Epoch 169/200] [Batch 60/235] [D loss: -0.035952] [G loss: 0.628977]\n",
      "[Epoch 169/200] [Batch 65/235] [D loss: -0.006671] [G loss: 1.095116]\n",
      "[Epoch 169/200] [Batch 70/235] [D loss: 0.021032] [G loss: 0.354910]\n",
      "[Epoch 169/200] [Batch 75/235] [D loss: -0.046898] [G loss: -0.025456]\n",
      "[Epoch 169/200] [Batch 80/235] [D loss: -0.010630] [G loss: -0.214096]\n",
      "[Epoch 169/200] [Batch 85/235] [D loss: -0.019731] [G loss: 0.555003]\n",
      "[Epoch 169/200] [Batch 90/235] [D loss: -0.014263] [G loss: 0.248747]\n",
      "[Epoch 169/200] [Batch 95/235] [D loss: -0.048776] [G loss: 0.340425]\n",
      "[Epoch 169/200] [Batch 100/235] [D loss: -0.017246] [G loss: -0.970945]\n",
      "[Epoch 169/200] [Batch 105/235] [D loss: -0.004965] [G loss: -1.748613]\n",
      "[Epoch 169/200] [Batch 110/235] [D loss: -0.015657] [G loss: -1.040511]\n",
      "[Epoch 169/200] [Batch 115/235] [D loss: -0.013553] [G loss: 0.259469]\n",
      "[Epoch 169/200] [Batch 120/235] [D loss: -0.019735] [G loss: 0.903091]\n",
      "[Epoch 169/200] [Batch 125/235] [D loss: -0.018578] [G loss: 0.638633]\n",
      "[Epoch 169/200] [Batch 130/235] [D loss: -0.013419] [G loss: -0.056011]\n",
      "[Epoch 169/200] [Batch 135/235] [D loss: -0.021540] [G loss: -1.042107]\n",
      "[Epoch 169/200] [Batch 140/235] [D loss: -0.016589] [G loss: 0.227506]\n",
      "[Epoch 169/200] [Batch 145/235] [D loss: -0.004431] [G loss: -0.158359]\n",
      "[Epoch 169/200] [Batch 150/235] [D loss: -0.013482] [G loss: -0.068721]\n",
      "[Epoch 169/200] [Batch 155/235] [D loss: -0.031405] [G loss: 1.318099]\n",
      "[Epoch 169/200] [Batch 160/235] [D loss: -0.022113] [G loss: 1.039029]\n",
      "[Epoch 169/200] [Batch 165/235] [D loss: -0.008112] [G loss: -0.294656]\n",
      "[Epoch 169/200] [Batch 170/235] [D loss: -0.016262] [G loss: -0.666627]\n",
      "[Epoch 169/200] [Batch 175/235] [D loss: -0.008824] [G loss: -0.050134]\n",
      "[Epoch 169/200] [Batch 180/235] [D loss: -0.017755] [G loss: 0.030230]\n",
      "[Epoch 169/200] [Batch 185/235] [D loss: -0.029856] [G loss: -0.188273]\n",
      "[Epoch 169/200] [Batch 190/235] [D loss: -0.006337] [G loss: 0.142610]\n",
      "[Epoch 169/200] [Batch 195/235] [D loss: -0.006367] [G loss: -0.144750]\n",
      "[Epoch 169/200] [Batch 200/235] [D loss: -0.019090] [G loss: -0.515227]\n",
      "[Epoch 169/200] [Batch 205/235] [D loss: -0.012650] [G loss: 0.254104]\n",
      "[Epoch 169/200] [Batch 210/235] [D loss: -0.018733] [G loss: 1.141350]\n",
      "[Epoch 169/200] [Batch 215/235] [D loss: -0.028742] [G loss: 1.283744]\n",
      "[Epoch 169/200] [Batch 220/235] [D loss: 0.015008] [G loss: 0.105015]\n",
      "[Epoch 169/200] [Batch 225/235] [D loss: -0.008927] [G loss: -0.495107]\n",
      "[Epoch 169/200] [Batch 230/235] [D loss: -0.028147] [G loss: -0.922263]\n",
      "[Epoch 170/200] [Batch 0/235] [D loss: -0.030961] [G loss: -0.923995]\n",
      "[Epoch 170/200] [Batch 5/235] [D loss: -0.029993] [G loss: 0.829977]\n",
      "[Epoch 170/200] [Batch 10/235] [D loss: -0.048041] [G loss: 1.953909]\n",
      "[Epoch 170/200] [Batch 15/235] [D loss: -0.013861] [G loss: 0.021736]\n",
      "[Epoch 170/200] [Batch 20/235] [D loss: -0.024902] [G loss: -0.961169]\n",
      "[Epoch 170/200] [Batch 25/235] [D loss: -0.014758] [G loss: -0.941794]\n",
      "[Epoch 170/200] [Batch 30/235] [D loss: -0.011452] [G loss: 0.335008]\n",
      "[Epoch 170/200] [Batch 35/235] [D loss: -0.026026] [G loss: 1.211432]\n",
      "[Epoch 170/200] [Batch 40/235] [D loss: -0.014722] [G loss: -0.273184]\n",
      "[Epoch 170/200] [Batch 45/235] [D loss: -0.010489] [G loss: -0.880877]\n",
      "[Epoch 170/200] [Batch 50/235] [D loss: -0.007552] [G loss: -0.056111]\n",
      "[Epoch 170/200] [Batch 55/235] [D loss: -0.027650] [G loss: 1.069535]\n",
      "[Epoch 170/200] [Batch 60/235] [D loss: -0.019082] [G loss: 0.031768]\n",
      "[Epoch 170/200] [Batch 65/235] [D loss: -0.017356] [G loss: -0.454625]\n",
      "[Epoch 170/200] [Batch 70/235] [D loss: -0.020969] [G loss: -0.960593]\n",
      "[Epoch 170/200] [Batch 75/235] [D loss: -0.015565] [G loss: 1.262610]\n",
      "[Epoch 170/200] [Batch 80/235] [D loss: -0.032858] [G loss: 1.884761]\n",
      "[Epoch 170/200] [Batch 85/235] [D loss: -0.005237] [G loss: -0.111778]\n",
      "[Epoch 170/200] [Batch 90/235] [D loss: -0.023657] [G loss: -1.534055]\n",
      "[Epoch 170/200] [Batch 95/235] [D loss: -0.013035] [G loss: -0.948277]\n",
      "[Epoch 170/200] [Batch 100/235] [D loss: -0.040168] [G loss: 1.398022]\n",
      "[Epoch 170/200] [Batch 105/235] [D loss: -0.038766] [G loss: 0.846041]\n",
      "[Epoch 170/200] [Batch 110/235] [D loss: 0.000720] [G loss: -0.455179]\n",
      "[Epoch 170/200] [Batch 115/235] [D loss: -0.022460] [G loss: -1.192715]\n",
      "[Epoch 170/200] [Batch 120/235] [D loss: -0.013162] [G loss: 0.331055]\n",
      "[Epoch 170/200] [Batch 125/235] [D loss: -0.037312] [G loss: 0.613708]\n",
      "[Epoch 170/200] [Batch 130/235] [D loss: -0.031127] [G loss: 0.803285]\n",
      "[Epoch 170/200] [Batch 135/235] [D loss: -0.000877] [G loss: -0.084754]\n",
      "[Epoch 170/200] [Batch 140/235] [D loss: -0.006947] [G loss: -0.033537]\n",
      "[Epoch 170/200] [Batch 145/235] [D loss: -0.018824] [G loss: -0.899828]\n",
      "[Epoch 170/200] [Batch 150/235] [D loss: -0.024047] [G loss: -0.154233]\n",
      "[Epoch 170/200] [Batch 155/235] [D loss: -0.040580] [G loss: 1.606033]\n",
      "[Epoch 170/200] [Batch 160/235] [D loss: -0.019120] [G loss: -0.200844]\n",
      "[Epoch 170/200] [Batch 165/235] [D loss: -0.014329] [G loss: -0.760873]\n",
      "[Epoch 170/200] [Batch 170/235] [D loss: -0.012872] [G loss: -0.589679]\n",
      "[Epoch 170/200] [Batch 175/235] [D loss: -0.016151] [G loss: -0.186735]\n",
      "[Epoch 170/200] [Batch 180/235] [D loss: -0.029949] [G loss: 1.936756]\n",
      "[Epoch 170/200] [Batch 185/235] [D loss: -0.028135] [G loss: 2.081356]\n",
      "[Epoch 170/200] [Batch 190/235] [D loss: -0.019820] [G loss: -0.797402]\n",
      "[Epoch 170/200] [Batch 195/235] [D loss: 0.005664] [G loss: -0.904267]\n",
      "[Epoch 170/200] [Batch 200/235] [D loss: -0.020659] [G loss: -0.589632]\n",
      "[Epoch 170/200] [Batch 205/235] [D loss: -0.015884] [G loss: -0.564466]\n",
      "[Epoch 170/200] [Batch 210/235] [D loss: -0.020421] [G loss: 0.870030]\n",
      "[Epoch 170/200] [Batch 215/235] [D loss: -0.009420] [G loss: 0.958290]\n",
      "[Epoch 170/200] [Batch 220/235] [D loss: -0.009648] [G loss: 0.502940]\n",
      "[Epoch 170/200] [Batch 225/235] [D loss: -0.030662] [G loss: -0.778429]\n",
      "[Epoch 170/200] [Batch 230/235] [D loss: -0.023580] [G loss: -0.984990]\n",
      "[Epoch 171/200] [Batch 0/235] [D loss: -0.016421] [G loss: 0.526029]\n",
      "[Epoch 171/200] [Batch 5/235] [D loss: -0.044200] [G loss: 1.771787]\n",
      "[Epoch 171/200] [Batch 10/235] [D loss: 0.002140] [G loss: -0.576670]\n",
      "[Epoch 171/200] [Batch 15/235] [D loss: -0.031707] [G loss: -1.741687]\n",
      "[Epoch 171/200] [Batch 20/235] [D loss: -0.010497] [G loss: -0.866427]\n",
      "[Epoch 171/200] [Batch 25/235] [D loss: -0.011040] [G loss: 0.722933]\n",
      "[Epoch 171/200] [Batch 30/235] [D loss: -0.040191] [G loss: 1.429292]\n",
      "[Epoch 171/200] [Batch 35/235] [D loss: -0.009858] [G loss: 0.587449]\n",
      "[Epoch 171/200] [Batch 40/235] [D loss: -0.022991] [G loss: -0.931119]\n",
      "[Epoch 171/200] [Batch 45/235] [D loss: -0.006431] [G loss: -0.907374]\n",
      "[Epoch 171/200] [Batch 50/235] [D loss: -0.020273] [G loss: -0.072902]\n",
      "[Epoch 171/200] [Batch 55/235] [D loss: -0.019279] [G loss: 0.608532]\n",
      "[Epoch 171/200] [Batch 60/235] [D loss: 0.000100] [G loss: -0.123959]\n",
      "[Epoch 171/200] [Batch 65/235] [D loss: -0.051914] [G loss: 0.422037]\n",
      "[Epoch 171/200] [Batch 70/235] [D loss: -0.019353] [G loss: -0.275016]\n",
      "[Epoch 171/200] [Batch 75/235] [D loss: -0.022889] [G loss: 0.169607]\n",
      "[Epoch 171/200] [Batch 80/235] [D loss: -0.029510] [G loss: 0.071232]\n",
      "[Epoch 171/200] [Batch 85/235] [D loss: -0.028311] [G loss: -0.083400]\n",
      "[Epoch 171/200] [Batch 90/235] [D loss: -0.000066] [G loss: 0.750942]\n",
      "[Epoch 171/200] [Batch 95/235] [D loss: -0.041608] [G loss: 0.947003]\n",
      "[Epoch 171/200] [Batch 100/235] [D loss: -0.034394] [G loss: -0.167419]\n",
      "[Epoch 171/200] [Batch 105/235] [D loss: -0.054568] [G loss: -0.513563]\n",
      "[Epoch 171/200] [Batch 110/235] [D loss: 0.019046] [G loss: -0.261495]\n",
      "[Epoch 171/200] [Batch 115/235] [D loss: -0.020365] [G loss: 0.615431]\n",
      "[Epoch 171/200] [Batch 120/235] [D loss: -0.007424] [G loss: 0.885669]\n",
      "[Epoch 171/200] [Batch 125/235] [D loss: 0.019409] [G loss: 0.585024]\n",
      "[Epoch 171/200] [Batch 130/235] [D loss: -0.013894] [G loss: -0.562933]\n",
      "[Epoch 171/200] [Batch 135/235] [D loss: -0.006658] [G loss: -0.367795]\n",
      "[Epoch 171/200] [Batch 140/235] [D loss: -0.019254] [G loss: -0.212544]\n",
      "[Epoch 171/200] [Batch 145/235] [D loss: -0.012582] [G loss: -0.262019]\n",
      "[Epoch 171/200] [Batch 150/235] [D loss: -0.044608] [G loss: 1.029186]\n",
      "[Epoch 171/200] [Batch 155/235] [D loss: -0.027625] [G loss: 0.673118]\n",
      "[Epoch 171/200] [Batch 160/235] [D loss: -0.024068] [G loss: -0.022230]\n",
      "[Epoch 171/200] [Batch 165/235] [D loss: -0.049122] [G loss: -0.880857]\n",
      "[Epoch 171/200] [Batch 170/235] [D loss: -0.000560] [G loss: -0.289912]\n",
      "[Epoch 171/200] [Batch 175/235] [D loss: -0.020131] [G loss: 0.345741]\n",
      "[Epoch 171/200] [Batch 180/235] [D loss: -0.123429] [G loss: 0.650801]\n",
      "[Epoch 171/200] [Batch 185/235] [D loss: -0.018559] [G loss: -0.829996]\n",
      "[Epoch 171/200] [Batch 190/235] [D loss: -0.029811] [G loss: -0.377346]\n",
      "[Epoch 171/200] [Batch 195/235] [D loss: -0.003163] [G loss: 0.104423]\n",
      "[Epoch 171/200] [Batch 200/235] [D loss: -0.010538] [G loss: -0.506913]\n",
      "[Epoch 171/200] [Batch 205/235] [D loss: -0.006841] [G loss: -0.630289]\n",
      "[Epoch 171/200] [Batch 210/235] [D loss: -0.002577] [G loss: -0.783679]\n",
      "[Epoch 171/200] [Batch 215/235] [D loss: -0.006237] [G loss: -0.232865]\n",
      "[Epoch 171/200] [Batch 220/235] [D loss: -0.005543] [G loss: 0.347445]\n",
      "[Epoch 171/200] [Batch 225/235] [D loss: -0.009022] [G loss: 0.737723]\n",
      "[Epoch 171/200] [Batch 230/235] [D loss: -0.025380] [G loss: 1.283228]\n",
      "[Epoch 172/200] [Batch 0/235] [D loss: -0.010622] [G loss: 1.686994]\n",
      "[Epoch 172/200] [Batch 5/235] [D loss: -0.006756] [G loss: 0.637452]\n",
      "[Epoch 172/200] [Batch 10/235] [D loss: -0.005887] [G loss: 0.178055]\n",
      "[Epoch 172/200] [Batch 15/235] [D loss: -0.015521] [G loss: 0.090166]\n",
      "[Epoch 172/200] [Batch 20/235] [D loss: -0.013848] [G loss: 0.342727]\n",
      "[Epoch 172/200] [Batch 25/235] [D loss: -0.017161] [G loss: 0.405183]\n",
      "[Epoch 172/200] [Batch 30/235] [D loss: -0.013623] [G loss: 0.570133]\n",
      "[Epoch 172/200] [Batch 35/235] [D loss: -0.026276] [G loss: -0.360394]\n",
      "[Epoch 172/200] [Batch 40/235] [D loss: -0.029697] [G loss: -0.203702]\n",
      "[Epoch 172/200] [Batch 45/235] [D loss: -0.031565] [G loss: -1.198639]\n",
      "[Epoch 172/200] [Batch 50/235] [D loss: -0.071734] [G loss: 0.458397]\n",
      "[Epoch 172/200] [Batch 55/235] [D loss: -0.011435] [G loss: -0.053335]\n",
      "[Epoch 172/200] [Batch 60/235] [D loss: -0.077124] [G loss: 0.002800]\n",
      "[Epoch 172/200] [Batch 65/235] [D loss: 0.000816] [G loss: 0.410555]\n",
      "[Epoch 172/200] [Batch 70/235] [D loss: -0.022822] [G loss: 0.782882]\n",
      "[Epoch 172/200] [Batch 75/235] [D loss: -0.067976] [G loss: 1.080682]\n",
      "[Epoch 172/200] [Batch 80/235] [D loss: -0.007182] [G loss: 0.859236]\n",
      "[Epoch 172/200] [Batch 85/235] [D loss: -0.006611] [G loss: -0.120950]\n",
      "[Epoch 172/200] [Batch 90/235] [D loss: -0.023903] [G loss: -0.675296]\n",
      "[Epoch 172/200] [Batch 95/235] [D loss: 0.000699] [G loss: -0.337404]\n",
      "[Epoch 172/200] [Batch 100/235] [D loss: -0.009068] [G loss: -0.015398]\n",
      "[Epoch 172/200] [Batch 105/235] [D loss: -0.010466] [G loss: 0.281336]\n",
      "[Epoch 172/200] [Batch 110/235] [D loss: -0.001189] [G loss: 0.153997]\n",
      "[Epoch 172/200] [Batch 115/235] [D loss: -0.009113] [G loss: 0.706781]\n",
      "[Epoch 172/200] [Batch 120/235] [D loss: 0.001430] [G loss: 0.564850]\n",
      "[Epoch 172/200] [Batch 125/235] [D loss: -0.002050] [G loss: 0.459034]\n",
      "[Epoch 172/200] [Batch 130/235] [D loss: -0.010093] [G loss: 0.508312]\n",
      "[Epoch 172/200] [Batch 135/235] [D loss: -0.017788] [G loss: 0.327913]\n",
      "[Epoch 172/200] [Batch 140/235] [D loss: -0.015474] [G loss: 0.018042]\n",
      "[Epoch 172/200] [Batch 145/235] [D loss: -0.038114] [G loss: -0.321253]\n",
      "[Epoch 172/200] [Batch 150/235] [D loss: -0.032052] [G loss: -0.500575]\n",
      "[Epoch 172/200] [Batch 155/235] [D loss: 0.014159] [G loss: -0.411001]\n",
      "[Epoch 172/200] [Batch 160/235] [D loss: 0.021839] [G loss: -0.381303]\n",
      "[Epoch 172/200] [Batch 165/235] [D loss: -0.019401] [G loss: -0.315232]\n",
      "[Epoch 172/200] [Batch 170/235] [D loss: -0.020639] [G loss: 0.004275]\n",
      "[Epoch 172/200] [Batch 175/235] [D loss: -0.005527] [G loss: 0.318496]\n",
      "[Epoch 172/200] [Batch 180/235] [D loss: 0.001827] [G loss: 0.208213]\n",
      "[Epoch 172/200] [Batch 185/235] [D loss: -0.033345] [G loss: 0.164814]\n",
      "[Epoch 172/200] [Batch 190/235] [D loss: -0.013963] [G loss: 0.250783]\n",
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      "[Epoch 175/200] [Batch 0/235] [D loss: -0.008221] [G loss: 0.553308]\n",
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      "[Epoch 175/200] [Batch 30/235] [D loss: -0.027948] [G loss: -0.322634]\n",
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      "[Epoch 175/200] [Batch 55/235] [D loss: -0.020890] [G loss: 0.148095]\n",
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      "[Epoch 175/200] [Batch 65/235] [D loss: -0.001074] [G loss: -0.139356]\n",
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      "[Epoch 175/200] [Batch 75/235] [D loss: -0.011280] [G loss: 0.003988]\n",
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      "[Epoch 175/200] [Batch 205/235] [D loss: -0.009435] [G loss: -0.260073]\n",
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      "[Epoch 176/200] [Batch 0/235] [D loss: -0.014405] [G loss: -0.136708]\n",
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      "[Epoch 176/200] [Batch 10/235] [D loss: -0.027331] [G loss: -0.216976]\n",
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      "[Epoch 176/200] [Batch 30/235] [D loss: -0.033139] [G loss: 0.119792]\n",
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      "[Epoch 176/200] [Batch 40/235] [D loss: -0.004024] [G loss: 0.515122]\n",
      "[Epoch 176/200] [Batch 45/235] [D loss: -0.003478] [G loss: 0.459917]\n",
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      "[Epoch 176/200] [Batch 55/235] [D loss: -0.003745] [G loss: 0.230789]\n",
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      "[Epoch 176/200] [Batch 65/235] [D loss: -0.007217] [G loss: -0.252673]\n",
      "[Epoch 176/200] [Batch 70/235] [D loss: -0.031945] [G loss: -0.060563]\n",
      "[Epoch 176/200] [Batch 75/235] [D loss: 0.000316] [G loss: 0.011621]\n",
      "[Epoch 176/200] [Batch 80/235] [D loss: -0.006831] [G loss: 0.220434]\n",
      "[Epoch 176/200] [Batch 85/235] [D loss: -0.015116] [G loss: 0.491750]\n",
      "[Epoch 176/200] [Batch 90/235] [D loss: -0.034383] [G loss: 0.506197]\n",
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      "[Epoch 176/200] [Batch 100/235] [D loss: -0.010917] [G loss: 0.395107]\n",
      "[Epoch 176/200] [Batch 105/235] [D loss: 0.009978] [G loss: -0.156819]\n",
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      "[Epoch 176/200] [Batch 120/235] [D loss: -0.016410] [G loss: -0.633554]\n",
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      "[Epoch 176/200] [Batch 130/235] [D loss: -0.005387] [G loss: -0.554563]\n",
      "[Epoch 176/200] [Batch 135/235] [D loss: 0.001276] [G loss: -0.078898]\n",
      "[Epoch 176/200] [Batch 140/235] [D loss: -0.020908] [G loss: 0.250573]\n",
      "[Epoch 176/200] [Batch 145/235] [D loss: -0.013845] [G loss: 0.170677]\n",
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      "[Epoch 176/200] [Batch 175/235] [D loss: -0.000976] [G loss: 0.214371]\n",
      "[Epoch 176/200] [Batch 180/235] [D loss: -0.004668] [G loss: -0.011927]\n",
      "[Epoch 176/200] [Batch 185/235] [D loss: -0.000256] [G loss: 0.312646]\n",
      "[Epoch 176/200] [Batch 190/235] [D loss: -0.015290] [G loss: -0.152477]\n",
      "[Epoch 176/200] [Batch 195/235] [D loss: -0.005337] [G loss: -0.155544]\n",
      "[Epoch 176/200] [Batch 200/235] [D loss: 0.002289] [G loss: -0.004886]\n",
      "[Epoch 176/200] [Batch 205/235] [D loss: -0.013152] [G loss: -0.154828]\n",
      "[Epoch 176/200] [Batch 210/235] [D loss: 0.002772] [G loss: -0.246220]\n",
      "[Epoch 176/200] [Batch 215/235] [D loss: -0.006711] [G loss: -0.289511]\n",
      "[Epoch 176/200] [Batch 220/235] [D loss: -0.023932] [G loss: -0.098143]\n",
      "[Epoch 176/200] [Batch 225/235] [D loss: -0.000707] [G loss: -0.284012]\n",
      "[Epoch 176/200] [Batch 230/235] [D loss: -0.017257] [G loss: -0.077677]\n",
      "[Epoch 177/200] [Batch 0/235] [D loss: 0.001135] [G loss: -0.305768]\n",
      "[Epoch 177/200] [Batch 5/235] [D loss: -0.013543] [G loss: -0.363675]\n",
      "[Epoch 177/200] [Batch 10/235] [D loss: -0.018823] [G loss: 0.063538]\n",
      "[Epoch 177/200] [Batch 15/235] [D loss: -0.012426] [G loss: 0.314231]\n",
      "[Epoch 177/200] [Batch 20/235] [D loss: -0.013771] [G loss: 0.359233]\n",
      "[Epoch 177/200] [Batch 25/235] [D loss: -0.012069] [G loss: 0.138062]\n",
      "[Epoch 177/200] [Batch 30/235] [D loss: -0.011914] [G loss: -0.085356]\n",
      "[Epoch 177/200] [Batch 35/235] [D loss: -0.009283] [G loss: -0.271038]\n",
      "[Epoch 177/200] [Batch 40/235] [D loss: -0.024182] [G loss: -0.511138]\n",
      "[Epoch 177/200] [Batch 45/235] [D loss: 0.005085] [G loss: -0.060511]\n",
      "[Epoch 177/200] [Batch 50/235] [D loss: -0.009556] [G loss: 0.272315]\n",
      "[Epoch 177/200] [Batch 55/235] [D loss: -0.004867] [G loss: 0.334812]\n",
      "[Epoch 177/200] [Batch 60/235] [D loss: -0.011716] [G loss: 0.546983]\n",
      "[Epoch 177/200] [Batch 65/235] [D loss: -0.014460] [G loss: 0.431877]\n",
      "[Epoch 177/200] [Batch 70/235] [D loss: -0.011500] [G loss: 0.136145]\n",
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      "[Epoch 181/200] [Batch 0/235] [D loss: -0.003477] [G loss: 0.844857]\n",
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      "[Epoch 181/200] [Batch 145/235] [D loss: -0.002722] [G loss: 0.139716]\n",
      "[Epoch 181/200] [Batch 150/235] [D loss: -0.003317] [G loss: -0.406723]\n",
      "[Epoch 181/200] [Batch 155/235] [D loss: -0.004744] [G loss: -0.666915]\n",
      "[Epoch 181/200] [Batch 160/235] [D loss: -0.010854] [G loss: -0.482660]\n",
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      "[Epoch 189/200] [Batch 0/235] [D loss: -0.015177] [G loss: -0.788649]\n",
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      "[Epoch 189/200] [Batch 150/235] [D loss: -0.018292] [G loss: -0.687730]\n",
      "[Epoch 189/200] [Batch 155/235] [D loss: -0.039006] [G loss: -0.913109]\n",
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      "[Epoch 190/200] [Batch 0/235] [D loss: 0.002327] [G loss: 0.717100]\n",
      "[Epoch 190/200] [Batch 5/235] [D loss: -0.029473] [G loss: -0.672008]\n",
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      "[Epoch 190/200] [Batch 15/235] [D loss: -0.016131] [G loss: 0.133798]\n",
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      "[Epoch 190/200] [Batch 70/235] [D loss: 0.008226] [G loss: -0.183441]\n",
      "[Epoch 190/200] [Batch 75/235] [D loss: -0.017488] [G loss: -0.051230]\n",
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      "[Epoch 190/200] [Batch 85/235] [D loss: -0.009145] [G loss: -0.082684]\n",
      "[Epoch 190/200] [Batch 90/235] [D loss: -0.023107] [G loss: -0.280014]\n",
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      "[Epoch 190/200] [Batch 100/235] [D loss: -0.012233] [G loss: 0.584273]\n",
      "[Epoch 190/200] [Batch 105/235] [D loss: -0.045333] [G loss: 1.420870]\n",
      "[Epoch 190/200] [Batch 110/235] [D loss: -0.019438] [G loss: 0.760583]\n",
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      "[Epoch 190/200] [Batch 120/235] [D loss: -0.036238] [G loss: -1.129441]\n",
      "[Epoch 190/200] [Batch 125/235] [D loss: -0.007139] [G loss: -1.364339]\n",
      "[Epoch 190/200] [Batch 130/235] [D loss: -0.000143] [G loss: -0.218554]\n",
      "[Epoch 190/200] [Batch 135/235] [D loss: -0.061078] [G loss: 1.813768]\n",
      "[Epoch 190/200] [Batch 140/235] [D loss: 0.008996] [G loss: 1.518278]\n",
      "[Epoch 190/200] [Batch 145/235] [D loss: 0.002356] [G loss: -0.719364]\n",
      "[Epoch 190/200] [Batch 150/235] [D loss: -0.006690] [G loss: -1.670051]\n",
      "[Epoch 190/200] [Batch 155/235] [D loss: -0.013538] [G loss: -2.226680]\n",
      "[Epoch 190/200] [Batch 160/235] [D loss: -0.012177] [G loss: -0.306501]\n",
      "[Epoch 190/200] [Batch 165/235] [D loss: -0.021389] [G loss: 1.024547]\n",
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      "[Epoch 190/200] [Batch 180/235] [D loss: -0.017825] [G loss: -1.261767]\n",
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      "[Epoch 192/200] [Batch 0/235] [D loss: -0.033694] [G loss: 0.013557]\n",
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      "[Epoch 193/200] [Batch 0/235] [D loss: 0.002282] [G loss: -0.378610]\n",
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      "[Epoch 193/200] [Batch 10/235] [D loss: -0.014420] [G loss: 0.219391]\n",
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      "[Epoch 193/200] [Batch 30/235] [D loss: -0.018028] [G loss: 0.947946]\n",
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      "[Epoch 193/200] [Batch 40/235] [D loss: -0.011142] [G loss: 0.233158]\n",
      "[Epoch 193/200] [Batch 45/235] [D loss: -0.027888] [G loss: -0.275356]\n",
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      "[Epoch 193/200] [Batch 60/235] [D loss: -0.022064] [G loss: 0.654070]\n",
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      "[Epoch 193/200] [Batch 70/235] [D loss: -0.026070] [G loss: 0.519854]\n",
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      "[Epoch 193/200] [Batch 80/235] [D loss: -0.004628] [G loss: 0.058933]\n",
      "[Epoch 193/200] [Batch 85/235] [D loss: -0.026399] [G loss: -0.276443]\n",
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      "[Epoch 193/200] [Batch 95/235] [D loss: -0.004465] [G loss: 0.249765]\n",
      "[Epoch 193/200] [Batch 100/235] [D loss: -0.032974] [G loss: -0.118951]\n",
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      "[Epoch 193/200] [Batch 155/235] [D loss: -0.020032] [G loss: -0.474420]\n",
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      "[Epoch 193/200] [Batch 195/235] [D loss: -0.020728] [G loss: -0.671520]\n",
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      "[Epoch 193/200] [Batch 215/235] [D loss: -0.007612] [G loss: -0.132782]\n",
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      "[Epoch 194/200] [Batch 0/235] [D loss: -0.009330] [G loss: 0.186635]\n",
      "[Epoch 194/200] [Batch 5/235] [D loss: -0.023024] [G loss: 0.934857]\n",
      "[Epoch 194/200] [Batch 10/235] [D loss: -0.026195] [G loss: 0.661794]\n",
      "[Epoch 194/200] [Batch 15/235] [D loss: -0.006153] [G loss: -0.099410]\n",
      "[Epoch 194/200] [Batch 20/235] [D loss: -0.013563] [G loss: 0.028913]\n",
      "[Epoch 194/200] [Batch 25/235] [D loss: -0.008176] [G loss: -0.097128]\n",
      "[Epoch 194/200] [Batch 30/235] [D loss: -0.005223] [G loss: -0.346068]\n",
      "[Epoch 194/200] [Batch 35/235] [D loss: -0.004742] [G loss: -0.511751]\n",
      "[Epoch 194/200] [Batch 40/235] [D loss: -0.009971] [G loss: -0.202840]\n",
      "[Epoch 194/200] [Batch 45/235] [D loss: -0.001862] [G loss: 0.038096]\n",
      "[Epoch 194/200] [Batch 50/235] [D loss: -0.003355] [G loss: -0.073884]\n",
      "[Epoch 194/200] [Batch 55/235] [D loss: -0.020551] [G loss: 0.224417]\n",
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      "[Epoch 194/200] [Batch 65/235] [D loss: -0.006276] [G loss: 0.117295]\n",
      "[Epoch 194/200] [Batch 70/235] [D loss: -0.027112] [G loss: 0.107840]\n",
      "[Epoch 194/200] [Batch 75/235] [D loss: -0.004443] [G loss: -0.236489]\n",
      "[Epoch 194/200] [Batch 80/235] [D loss: -0.005866] [G loss: -0.377691]\n",
      "[Epoch 194/200] [Batch 85/235] [D loss: -0.000986] [G loss: -0.196537]\n",
      "[Epoch 194/200] [Batch 90/235] [D loss: -0.007958] [G loss: 0.082992]\n",
      "[Epoch 194/200] [Batch 95/235] [D loss: -0.006909] [G loss: 0.216186]\n",
      "[Epoch 194/200] [Batch 100/235] [D loss: -0.007899] [G loss: 0.236391]\n",
      "[Epoch 194/200] [Batch 105/235] [D loss: -0.001466] [G loss: 0.182119]\n",
      "[Epoch 194/200] [Batch 110/235] [D loss: -0.005129] [G loss: -0.060266]\n",
      "[Epoch 194/200] [Batch 115/235] [D loss: -0.007295] [G loss: -0.261014]\n",
      "[Epoch 194/200] [Batch 120/235] [D loss: -0.003500] [G loss: -0.396746]\n",
      "[Epoch 194/200] [Batch 125/235] [D loss: -0.007074] [G loss: -0.588568]\n",
      "[Epoch 194/200] [Batch 130/235] [D loss: -0.009141] [G loss: -0.415151]\n",
      "[Epoch 194/200] [Batch 135/235] [D loss: -0.009301] [G loss: -0.210609]\n",
      "[Epoch 194/200] [Batch 140/235] [D loss: -0.003010] [G loss: -0.550162]\n",
      "[Epoch 194/200] [Batch 145/235] [D loss: -0.009092] [G loss: -0.679990]\n",
      "[Epoch 194/200] [Batch 150/235] [D loss: -0.013034] [G loss: 0.095293]\n",
      "[Epoch 194/200] [Batch 155/235] [D loss: -0.005808] [G loss: 0.116825]\n",
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      "[Epoch 194/200] [Batch 165/235] [D loss: -0.043935] [G loss: 0.634633]\n",
      "[Epoch 194/200] [Batch 170/235] [D loss: -0.001333] [G loss: -0.453070]\n",
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      "[Epoch 194/200] [Batch 190/235] [D loss: -0.022400] [G loss: 1.083420]\n",
      "[Epoch 194/200] [Batch 195/235] [D loss: 0.021554] [G loss: 1.114356]\n",
      "[Epoch 194/200] [Batch 200/235] [D loss: 0.000169] [G loss: 0.512242]\n",
      "[Epoch 194/200] [Batch 205/235] [D loss: -0.021225] [G loss: -0.573929]\n",
      "[Epoch 194/200] [Batch 210/235] [D loss: -0.006694] [G loss: -0.431583]\n",
      "[Epoch 194/200] [Batch 215/235] [D loss: 0.020640] [G loss: 0.145343]\n",
      "[Epoch 194/200] [Batch 220/235] [D loss: -0.020841] [G loss: 1.173912]\n",
      "[Epoch 194/200] [Batch 225/235] [D loss: -0.025546] [G loss: 1.045176]\n",
      "[Epoch 194/200] [Batch 230/235] [D loss: 0.000024] [G loss: -0.224946]\n",
      "[Epoch 195/200] [Batch 0/235] [D loss: -0.047892] [G loss: -0.840545]\n",
      "[Epoch 195/200] [Batch 5/235] [D loss: -0.003860] [G loss: -0.372874]\n",
      "[Epoch 195/200] [Batch 10/235] [D loss: -0.015542] [G loss: 0.014909]\n",
      "[Epoch 195/200] [Batch 15/235] [D loss: -0.030666] [G loss: 0.392962]\n",
      "[Epoch 195/200] [Batch 20/235] [D loss: -0.008058] [G loss: -0.252800]\n",
      "[Epoch 195/200] [Batch 25/235] [D loss: -0.046459] [G loss: -0.989205]\n",
      "[Epoch 195/200] [Batch 30/235] [D loss: -0.007863] [G loss: 0.581006]\n",
      "[Epoch 195/200] [Batch 35/235] [D loss: -0.015361] [G loss: 1.257891]\n",
      "[Epoch 195/200] [Batch 40/235] [D loss: -0.011301] [G loss: 1.706646]\n",
      "[Epoch 195/200] [Batch 45/235] [D loss: -0.006390] [G loss: 0.283068]\n",
      "[Epoch 195/200] [Batch 50/235] [D loss: -0.016911] [G loss: -0.847563]\n",
      "[Epoch 195/200] [Batch 55/235] [D loss: -0.014776] [G loss: 0.171985]\n",
      "[Epoch 195/200] [Batch 60/235] [D loss: -0.053481] [G loss: 0.484999]\n",
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      "[Epoch 198/200] [Batch 0/235] [D loss: 0.008308] [G loss: -0.619468]\n",
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      "[Epoch 198/200] [Batch 70/235] [D loss: -0.002366] [G loss: -0.413608]\n",
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      "[Epoch 198/200] [Batch 80/235] [D loss: -0.004800] [G loss: 0.055659]\n",
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      "[Epoch 198/200] [Batch 90/235] [D loss: -0.018063] [G loss: 0.479705]\n",
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      "[Epoch 198/200] [Batch 100/235] [D loss: -0.006726] [G loss: 0.882396]\n",
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      "[Epoch 198/200] [Batch 115/235] [D loss: -0.000110] [G loss: -0.440677]\n",
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      "[Epoch 198/200] [Batch 125/235] [D loss: -0.006928] [G loss: -0.447748]\n",
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      "[Epoch 198/200] [Batch 145/235] [D loss: -0.004952] [G loss: 0.109813]\n",
      "[Epoch 198/200] [Batch 150/235] [D loss: -0.006639] [G loss: -0.575674]\n",
      "[Epoch 198/200] [Batch 155/235] [D loss: -0.019465] [G loss: -0.860004]\n",
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      "[Epoch 198/200] [Batch 165/235] [D loss: -0.020322] [G loss: -0.104600]\n",
      "[Epoch 198/200] [Batch 170/235] [D loss: -0.018896] [G loss: 0.810440]\n",
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      "[Epoch 198/200] [Batch 185/235] [D loss: -0.012459] [G loss: -1.057612]\n",
      "[Epoch 198/200] [Batch 190/235] [D loss: -0.013637] [G loss: -1.587570]\n",
      "[Epoch 198/200] [Batch 195/235] [D loss: -0.004210] [G loss: -0.251204]\n",
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      "[Epoch 199/200] [Batch 0/235] [D loss: -0.002854] [G loss: 0.519738]\n",
      "[Epoch 199/200] [Batch 5/235] [D loss: -0.012118] [G loss: -0.543556]\n",
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      "[Epoch 199/200] [Batch 15/235] [D loss: -0.003455] [G loss: -0.295916]\n",
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      "[Epoch 199/200] [Batch 30/235] [D loss: 0.028485] [G loss: 0.807802]\n",
      "[Epoch 199/200] [Batch 35/235] [D loss: -0.017631] [G loss: -0.392409]\n",
      "[Epoch 199/200] [Batch 40/235] [D loss: -0.028319] [G loss: -1.112258]\n",
      "[Epoch 199/200] [Batch 45/235] [D loss: 0.004323] [G loss: -0.581231]\n",
      "[Epoch 199/200] [Batch 50/235] [D loss: -0.021208] [G loss: -0.085829]\n",
      "[Epoch 199/200] [Batch 55/235] [D loss: -0.025349] [G loss: 0.154076]\n",
      "[Epoch 199/200] [Batch 60/235] [D loss: -0.001011] [G loss: 0.187798]\n",
      "[Epoch 199/200] [Batch 65/235] [D loss: -0.008994] [G loss: -0.272407]\n",
      "[Epoch 199/200] [Batch 70/235] [D loss: -0.015870] [G loss: -0.744881]\n",
      "[Epoch 199/200] [Batch 75/235] [D loss: -0.005200] [G loss: 0.149571]\n",
      "[Epoch 199/200] [Batch 80/235] [D loss: -0.036009] [G loss: 0.968646]\n",
      "[Epoch 199/200] [Batch 85/235] [D loss: -0.012860] [G loss: 0.939407]\n",
      "[Epoch 199/200] [Batch 90/235] [D loss: -0.025662] [G loss: 0.935729]\n",
      "[Epoch 199/200] [Batch 95/235] [D loss: -0.006315] [G loss: -0.669066]\n",
      "[Epoch 199/200] [Batch 100/235] [D loss: -0.021004] [G loss: -1.571611]\n",
      "[Epoch 199/200] [Batch 105/235] [D loss: 0.001955] [G loss: -0.296377]\n",
      "[Epoch 199/200] [Batch 110/235] [D loss: -0.021079] [G loss: 0.801669]\n",
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      "[Epoch 199/200] [Batch 125/235] [D loss: -0.015622] [G loss: -0.829391]\n",
      "[Epoch 199/200] [Batch 130/235] [D loss: -0.016630] [G loss: -1.320049]\n",
      "[Epoch 199/200] [Batch 135/235] [D loss: -0.007201] [G loss: 0.254868]\n",
      "[Epoch 199/200] [Batch 140/235] [D loss: -0.051983] [G loss: 1.659492]\n",
      "[Epoch 199/200] [Batch 145/235] [D loss: -0.006314] [G loss: 1.567831]\n",
      "[Epoch 199/200] [Batch 150/235] [D loss: 0.004618] [G loss: 0.051359]\n",
      "[Epoch 199/200] [Batch 155/235] [D loss: -0.011041] [G loss: -0.758503]\n",
      "[Epoch 199/200] [Batch 160/235] [D loss: -0.031571] [G loss: -1.422453]\n",
      "[Epoch 199/200] [Batch 165/235] [D loss: -0.029699] [G loss: -0.425996]\n",
      "[Epoch 199/200] [Batch 170/235] [D loss: -0.046547] [G loss: 1.542827]\n",
      "[Epoch 199/200] [Batch 175/235] [D loss: 0.000928] [G loss: 0.973031]\n",
      "[Epoch 199/200] [Batch 180/235] [D loss: -0.005222] [G loss: -0.138873]\n",
      "[Epoch 199/200] [Batch 185/235] [D loss: -0.042284] [G loss: -1.069046]\n",
      "[Epoch 199/200] [Batch 190/235] [D loss: 0.010381] [G loss: -0.271748]\n",
      "[Epoch 199/200] [Batch 195/235] [D loss: -0.020250] [G loss: 0.841184]\n",
      "[Epoch 199/200] [Batch 200/235] [D loss: 0.002744] [G loss: 0.662837]\n",
      "[Epoch 199/200] [Batch 205/235] [D loss: -0.000532] [G loss: -0.042691]\n",
      "[Epoch 199/200] [Batch 210/235] [D loss: -0.031875] [G loss: -0.088909]\n",
      "[Epoch 199/200] [Batch 215/235] [D loss: -0.004872] [G loss: -0.534614]\n",
      "[Epoch 199/200] [Batch 220/235] [D loss: -0.025893] [G loss: -0.013984]\n",
      "[Epoch 199/200] [Batch 225/235] [D loss: 0.000405] [G loss: -0.324157]\n",
      "[Epoch 199/200] [Batch 230/235] [D loss: -0.019336] [G loss: -0.834489]\n"
     ]
    }
   ],
   "source": [
    "batches_done = 0\n",
    "for epoch in range(opt.n_epochs):\n",
    "\n",
    "    for i, (imgs, _) in enumerate(dataloader):\n",
    "\n",
    "        # Configure input\n",
    "        real_imgs = Variable(imgs.type(Tensor))\n",
    "\n",
    "        # ---------------------\n",
    "        #  Train Discriminator\n",
    "        # ---------------------\n",
    "\n",
    "        optimizer_D.zero_grad()\n",
    "\n",
    "        # Sample noise as generator input\n",
    "        z = Variable(Tensor(np.random.normal(0, 1, (imgs.shape[0], opt.latent_dim))))\n",
    "\n",
    "        # Generate a batch of images\n",
    "        fake_imgs = generator(z).detach()\n",
    "        # Adversarial loss\n",
    "        loss_D = -torch.mean(discriminator(real_imgs)) + torch.mean(discriminator(fake_imgs))\n",
    "\n",
    "        loss_D.backward()\n",
    "        optimizer_D.step()\n",
    "\n",
    "        # Clip weights of discriminator\n",
    "        for p in discriminator.parameters():\n",
    "            p.data.clamp_(-opt.clip_value, opt.clip_value)\n",
    "\n",
    "        # Train the generator every n_critic iterations\n",
    "        if i % opt.n_critic == 0:\n",
    "\n",
    "            # -----------------\n",
    "            #  Train Generator\n",
    "            # -----------------\n",
    "\n",
    "            optimizer_G.zero_grad()\n",
    "\n",
    "            # Generate a batch of images\n",
    "            gen_imgs = generator(z)\n",
    "            # Adversarial loss\n",
    "            loss_G = -torch.mean(discriminator(gen_imgs))\n",
    "\n",
    "            loss_G.backward()\n",
    "            optimizer_G.step()\n",
    "\n",
    "            print(\n",
    "                \"[Epoch %d/%d] [Batch %d/%d] [D loss: %f] [G loss: %f]\"\n",
    "                % (epoch, opt.n_epochs, batches_done % len(dataloader), len(dataloader), loss_D.item(), loss_G.item())\n",
    "            )\n",
    "\n",
    "        if batches_done % opt.sample_interval == 0:\n",
    "            save_image(gen_imgs.data[:25], \"images2/%d.png\" % batches_done, nrow=5, normalize=True)\n",
    "        batches_done += 1"
   ]
  }
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